Polyubiquitin chain assembly and organization determine the dynamics of protein activation and degradation

Protein degradation via ubiquitination is a major proteolytic mechanism in cells. Once a protein is destined for degradation, it is tagged by multiple ubiquitin (Ub) molecules. The synthesized polyubiquitin chains can be recognized by the 26S proteosome where proteins are degraded. These chains form through multiple ubiquitination cycles that are similar to multi-site phosphorylation cycles. As kinases and phosphatases, two opposing enzymes (E3 ligases and deubiquitinases DUBs) catalyze (de)ubiquitination cycles. Although multi-ubiquitination cycles are fundamental mechanisms of controlling protein concentrations within a cell, their dynamics have never been explored. Here, we fill this knowledge gap. We show that under permissive physiological conditions, the formation of polyubiquitin chain of length greater than two and subsequent degradation of the ubiquitinated protein, which is balanced by protein synthesis, can display bistable, switch-like responses. Interestingly, the occurrence of bistability becomes pronounced, as the chain grows, giving rise to “all-or-none” regulation at the protein levels. We give predictions of protein distributions under bistable regime awaiting experimental verification. Importantly, we show for the first time that sustained oscillations can robustly arise in the process of formation of ubiquitin chain, largely due to the degradation of the target protein. This new feature is opposite to the properties of multi-site phosphorylation cycles, which are incapable of generating oscillation if the total abundance of interconverted protein forms is conserved. We derive structural and kinetic constraints for the emergence of oscillations, indicating that a competition between different substrate forms and the E3 and DUB is critical for oscillation. Our work provides the first detailed elucidation of the dynamical features brought about by different molecular setups of the polyubiquitin chain assembly process responsible for protein degradation

Principles and theory of protein-based pattern formation

Biological systems perform functions by the orchestrated interplay of many small components without a "conductor." Such self-organization pervades life on many scales, from the subcellular level to populations of many organisms and whole ecosystems. On the intracellular level, protein-based pattern formation coordinates and instructs functions like cell division, differentiation and motility. A key feature of protein-based pattern formation is that the total numbers of the involved proteins remain constant on the timescale of pattern formation. The overarching theme of this thesis is the profound impact of this mass-conservation property on pattern formation and how one can harness mass conservation to understand the underlying physical principles. The central insight is that changes in local densities shift local reactive equilibria, and thus induce concentration gradients which, in turn, drive diffusive transport of mass. For two-component systems, this dynamic interplay can be captured by simple geometric objects in the (low-dimensional) phase space of chemical concentrations. On this phase-space level, physical insight can be gained from geometric criteria and graphical constructions. Moreover, we introduce the notion of regional (in)stabilities, which allows one to characterize the dynamics in the highly nonlinear regime reveals an inherent connection between Turing instability and stimulus-induced pattern formation. The insights gained for conceptual two-component systems can be generalized to systems with more components and several conserved masses. In the minimal setting of two diffusively coupled "reactors," the full dynamics can be embedded in the phase-space of redistributed masses where the phase space flow is organized by surfaces of local reactive equilibria. Building on the phase-space analysis for two component systems, we develop a new approach to the important open problem of wavelength selection in the highly nonlinear regime. We show that two-component reaction–diffusion systems always exhibit uninterrupted coarsening (the continual growth of the characteristic length scale) of patterns if they are strictly mass conserving. Selection of a finite wavelength emerges due to weakly broken mass-conservation, or coupling to additional components, which counteract and stop the competition instability that drives coarsening. For complex dynamical phenomena like wave patterns and the transition to spatiotemporal chaos, an analysis in terms of local equilibria and their stability properties provides a powerful tool to interpret data from numerical simulations and experiments, and to reveal the underlying physical mechanisms. In collaborations with different experimental labs, we studied the Min system of Escherichia coli. A central insight from these investigations is that bulk-surface coupling imparts a strong dependence of pattern formation on the geometry of the spatial confinement, which explains the qualitatively different dynamics observed inside cells compared to in vitro reconstitutions. By theoretically studying the polarization machinery in budding yeast and testing predictions in collaboration with experimentalists, we found that this functional module implements several redundant polarization mechanisms that depend on different subsets of proteins. Taken together, our work reveals unifying principles underlying biological self-organization and elucidates how microscopic interaction rules and physical constraints collectively lead to specific biological functions.Biologische Systeme führen Funktionen durch das orchestrierte Zusammenspiel vieler kleiner Komponenten ohne einen "Dirigenten" aus. Solche Selbstorganisation durchdringt das Leben auf vielen Skalen, von der subzellulären Ebene bis zu Populationen vieler Organismen und ganzen Ökosystemen. Auf der intrazellulären Ebene koordiniert und instruieren proteinbasierte Muster Funktionen wie Zellteilung, Differenzierung und Motilität. Ein wesentliches Merkmal der proteinbasierten Musterbildung ist, dass die Gesamtzahl der beteiligten Proteine auf der Zeitskala der Musterbildung konstant bleibt. Das übergreifende Thema dieser Arbeit ist es, den tiefgreifenden Einfluss dieser Massenerhaltung auf die Musterbildung zu untersuchen und Methoden zu entwickeln, die Massenerhaltung nutzen, um die zugrunde liegenden physikalischen Prinzipien von proteinbasierter Musterbildung zu verstehen. Die zentrale Erkenntnis ist, dass Änderungen der lokalen Dichten lokale reaktive Gleichgewichte verschieben und somit Konzentrationsgradienten induzieren, die wiederum den diffusiven Transport von Masse antreiben. Für Zweikomponentensysteme kann dieses dynamische Wechselspiel durch einfache geometrische Objekte im (niedrigdimensionalen) Phasenraum der chemischen Konzentrationen erfasst werden. Auf dieser Phasenraumebene können physikalische Erkenntnisse durch geometrische Kriterien und grafische Konstruktionen gewonnen werden. Darüber hinaus führen wir den Begriff der regionalen (In-)stabilität ein, der es erlaubt, die Dynamik im hochgradig nichtlinearen Regime zu charakterisieren und einen inhärenten Zusammenhang zwischen Turing-Instabilität und stimulusinduzierter Musterbildung aufzuzeigen. Die für konzeptionelle Zweikomponentensysteme gewonnenen Erkenntnisse können auf Systeme mit mehr Komponenten und mehreren erhaltenen Massen verallgemeinert werden. In der minimalen Fassung von zwei diffusiv gekoppelten "Reaktoren" kann die gesamte Dynamik in den Phasenraum umverteilter Massen eingebettet werden, wobei der Phasenraumfluss durch Flächen lokaler reaktiver Gleichgewichte organisiert wird. Aufbauend auf der Phasenraumanalyse für Zweikomponentensysteme entwickeln wir einen neuen Ansatz für die wichtige offene Fragestellung der Wellenängenselektion im hochgradig nichtlinearen Regime. Wir zeigen, dass "coarsening" (das stetige wachsen der charakteristischen Längenskala) von Mustern in Zweikomponentensystemen nie stoppt, wenn sie exakt massenerhaltend sind. Die Selektion einer endlichen Wellenlänge entsteht durch schwach gebrochene Massenerhaltung oder durch Kopplung an zusätzliche Komponenten. Diese Prozesse wirken der Masseumverteilung, die coarsening treibt, entgegen und stoppen so das coarsening. Bei komplexen dynamischen Phänomenen wie Wellenmustern und dem Übergang zu raumzeitlichen Chaos bietet eine Analyse in Bezug auf lokale Gleichgewichte und deren Stabilitätseigenschaften ein leistungsstarkes Werkzeug, um Daten aus numerischen Simulationen und Experimenten zu interpretieren und die zugrunde liegenden physikalischen Mechanismen aufzudecken. In Zusammenarbeit mit verschiedenen experimentellen Labors haben wir das Min-System von Escherichia coli untersucht. Eine zentrale Erkenntnis aus diesen Untersuchungen ist, dass die Kopplung zwischen Volumen und Oberfläche zu einer starken Abhängigkeit der Musterbildung von der räumlichen Geometrie führt. Das erklärt die qualitativ unterschiedliche Dynamik, die in Zellen im Vergleich zu in vitro Rekonstitutionen beobachtet wird. Durch die theoretische Untersuchung der Polarisationsmaschinerie in Hefezellen, kombiniert mit experimentellen Tests theoretischer Vorhersagen, haben wir herausgefunden, dass dieses Funktionsmodul mehrere redundante Polarisationsmechanismen implementiert, die von verschiedenen Untergruppen von Proteinen abhängen. Zusammengenommen beleuchtet unsere Arbeit die vereinheitlichenden Prinzipien, die der intrazellulären Selbstorganisation zugrunde liegen, und zeigt, wie mikroskopische Interaktionsregeln und physikalische Bedingungen gemeinsam zu spezifischen biologischen Funktionen führen

G protein-coupled receptor-mediated calcium signaling in astrocytes

Astrocytes express a large variety of G~protein-coupled receptors (GPCRs) which mediate the transduction of extracellular signals into intracellular calcium responses. This transduction is provided by a complex network of biochemical reactions which mobilizes a wealth of possible calcium-mobilizing second messenger molecules. Inositol 1,4,5-trisphosphate is probably the best known of these molecules whose enzymes for its production and degradation are nonetheless calcium-dependent. We present a biophysical modeling approach based on the assumption of Michaelis-Menten enzyme kinetics, to effectively describe GPCR-mediated astrocytic calcium signals. Our model is then used to study different mechanisms at play in stimulus encoding by shape and frequency of calcium oscillations in astrocytes.Comment: 35 pages, 6 figures, 1 table, 3 appendices (book chapter

Waves, ChIPs, GEMMs, gears, markers and maps:Computational systems biology from cell cycle oscillations to metabolic fluxes

This thesis discusses six scientific works within the fields of systems biology and bioinformatics. These works are unified in their conception of the cell as a system of integrated fluxes of mass and information, in the application of computational approaches to answer the questions at hand and in their aim for computation to drive new biological discoveries. The overarching theme is that by bringing computational methodologies in contact with quantitative experimental data, new principles can be proposed and/or tested that would not otherwise have been discovered. The first three chapters of this thesis focus on (the cell cycle of) budding yeast. Specifically, Ch. 2 deals with kinetic models for waves-of-cyclins. Ch. 3 concerns analysis of ChIP-exo experiments to retrieve the specific binding sites at gene promoters where Forkhead transcription factors Fkh1 and Fkh2 bind. Ch. 4 presents a web-based database and visualization tool which integrates a variety of sources of information concerning all protein-coding genes and allows users to craft specific and visualizations of the topology of interaction networks. The last three chapters of this thesis focus on that other process by which life produces more of itself: metabolism. Specifically, our focus is on thermodynamics and metabolic networks in acetogenic bacteria (Ch. 5) and human liver (Ch. 6-7). Ch. 5 is concerned with the concept of gear-shifting: an organism's hypothetical ability to express metabolic enzymes that result in different stoichiometric yields in order to navigate a trade-off between rate and yield. In Ch. 6 and 7 we discuss two approaches to deal partially with concentrations in flux balance analysis, i.e. in terms of serum concentrations of biomarkers (Ch. 6) and in terms of uptake fluxes and concentrations of medium metabolites and metabolic enzymes (Ch. 7). The six chapters present new datasets, provide novel tools, develop new models, propose novel (extensions of) computational methodologies and rationalize and assess existing methodologies. As such, this thesis provides a glance into the cutting-edge of biomedical research in this data-driven, computation-assisted age

Relating topology and dynamics in cell signaling networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 153-163).Cells are constantly bombarded with stimuli that they must sense, process, and interpret to make decisions. This capability is provided by interconnected signaling pathways. Many of the components and interactions within pathways have been identified, and it is becoming clear that the precise dynamics they generate are necessary for proper system function. However, our understanding of how pathways are interconnected to drive decisions is limited. We must overcoming this limitation to develop interventions that can fine tune a cell decision by modulating specific features of its constituent pathway's dynamics. How can we quantatively map a whole cell decision process? Answering this question requires addressing challenges at three scales: the detailed biochemistry of protein-protein interactions, the complex, interlocked feedback loops of transcriptionally regulated signaling pathways, and the multiple mechanisms of connection that link distinct pathways together into a full cell decision process. In this thesis, we address challenges at each level. We develop new computational approaches for identifying the interactions driving dynamics in protein-protein networks. Applied to the cyanobacterial clock, these approaches identify two coupled motifs that together provide independent control over oscillation phase and period. Using the p53 pathway as a model transcriptional network, we experimentally isolate and characterize dynamics from a core feedback loop in individual cells. A quantitative model of this signaling network predicts and rationalizes the distinct effects on dynamics of additional feedback loops and small molecule inhibitors. Finally, we demonstrated the feasibility of combining individual pathway models to map a whole cell decision: cell cycle arrest elicited by the mammalian DNA damage response. By coupling modeling and experiments, we used this combined perspective to uncover some new biology. We found that multiple arrest mechanisms must work together in a proper cell cycle arrest, and identified a new role for p21 in preventing G2 arrest, paradoxically through its action on G1 cyclins. This thesis demonstrates that we can quantitatively map the logic of cellular decisions, affording new insight and revealing points of control.by Jared E. Toettcher.Ph.D

Quantitative analysis of the receptor-induced apoptotic decision network

Thesis (Ph. D.)--Massachusetts Institute of Technology, Biological Engineering Division, 2008.Includes bibliographical references (p. 157-169).Cells use a complex web of protein signaling pathways to interpret extracellular cues and decide and execute cell fates such as survival, apoptosis, differentiation, and proliferation. Cell decisions can be triggered by subtle, transient signals that are context specific, making them hard to study by conventional experimental methods. In this thesis, we use a systems approach combining quantitative experiments with computational modeling and analysis to understand the regulation of the survival-vs-death decision. A second goal of this thesis was to develop modeling and analysis methods that enable study of signals that are transient or at intermediate activation levels. We addressed the challenge of balancing mechanistic detail and ease of interpretation in modeling by adapting fuzzy logic to analyze a previously published experimental dataset characterizing the dynamic behavior of kinase pathways governing apoptosis in human colon carcinoma cells. Simulations of our fuzzy logic model recapitulated most features of the data and generated several predictions involving pathway crosstalk and regulation. Fuzzy logic models are flexible, able to incorporate qualitative and noisy data, and powerful enough to generate not only quantitative predictions but also biological insights concerning operation of signaling networks. To study transient signals in differential-equation based models, we employed direct Lyapunov exponents (DLEs) to identify phase-space domains of high sensitivity to initial conditions. These domains delineate regions exhibiting qualitatively different transient activities that would be indistinguishable using steady-state analysis but which correspond to different outcomes.(cont.) We combine DLE analysis of a physicochemical model of receptor-mediated apoptosis with single cell data obtained by flow cytometry and FRET-based reporters in live-cell microscopy to classify conditions that alter the usage of two apoptosis pathways (Type I/II apoptosis). While it is generally thought that the control point for Type I/II occurs at the level of initiator caspase activation, we find that Type II cells can be converted to Type I by removal of XIAP, a regulator of effector caspases. Our study suggests that the classification of cells as Type I or II obscures a third variable category of cells that are highly sensitive to changes in the concentrations of key apoptotic network proteins.by Bree Beardsley Aldridge.Ph.D

Engineering a synthetic p53-Mdm2 network in budding yeast

p53 is among the most thoroughly studied proteins to date. Its tumour suppressor activity and the consideration that inactivation of the p53 pathway is a common, if not universal, feature of all human cancers, have gained it the interest of a multitude of researches seeking new therapies against this disease. As a consequence, p53 is at the centre of a feverish research and nowadays is reported to be involved in most cellular processes. Despite the vast amount of data published, much is yet to be unravelled about the mechanisms regulating the p53 signalling network. Indeed, the p53 network is extremely intricate and complex, and from a system biology point of view it can be seen as a series of interconnected negative and positive feedback loops, which can give rise to complex dynamics such as oscillations. In the combined effort to understand more of the biological meaning of these oscillations and to study the properties of this network motif from an engineering perspective, a synthetic p53 network has been built in budding yeast with the aim of studying the network in isolation while being embedded in living cells. p53 and most proteins in the network are absent from the budding yeast genome. This diminishes the likelihood of interferences on the engineered module from the cellular environment. Surprisingly, despite the evolutionary conservation of the ubiquitin pathway from yeast to humans, p53 ubiquitylation by the E3 ubiquitin ligase Mdm2 - an event central to the oscillatory dynamics of the system - does not appear to take place in budding yeast, even when the human E2 enzyme UbcH5B is exogenously expressed. p53 is instead sumoylated by Mdm2 and sumoylation dictates the co-localization of p53 and Mdm2 to a nuclear body reminiscent of human PML bodies. In conclusion, attempting to rebuild from scratch a simplified version of the intricate p53 network, isolating it from its natural context, has proven to be a very powerful means leading to unexpected findings, testifying the usefulness of the synthetic biology approach

Investigating homeostatic disruption by constitutive signals during biological ageing

PhD ThesisAgeing and disease can be understood in terms of a loss in biological homeostasis. This will often manifest as a constitutive elevation in the basal levels of biological entities. Examples include chronic inflammation, hormonal imbalances and oxidative stress. The ability of reactive oxygen species (ROS) to cause molecular damage has meant that chronic oxidative stress has been mostly studied from the point of view of being a source of toxicity to the cell. However, the known duality of ROS molecules as both damaging agents and cellular redox signals implies another perspective in the study of sustained oxidative stress. This is a perspective of studying oxidative stress as a constitutive signal within the cell. In this work a computational modelling approach is undertaken to examine how chronic oxidative stress can interfere with signal processing by redox signalling pathways in the cell. A primary outcome of this study is that constitutive signals can give rise to a ‘molecular habituation’ effect that can prime for a gradual loss of biological function. Experimental results obtained highlight the difficulties in testing for this effect in cell lines exposed to oxidative stress. However, further analysis suggests this phenomenon is likely to occur in different signalling pathways exposed to persistent signals and potentially at different levels of biological organisation.Centre for Integrated Research into Musculoskeletal Ageing (CIMA) and through them, Arthritis Research UK and the Medical Research Counc

Development of a non-contact blood rheometer using acoustic levitation and laser scattering techniques

Coagulopathy, a condition in which blood coagulation is impaired, can be inherited or result from a variety of conditions including severe trauma, illness or surgery. Perioperative monitoring of a patient’s coagulation status is important to identify coagulopathic patients. Thromboelastography or TEG remains the gold standard for whole blood coagulation monitoring. However, TEG suffers from certain well-documented drawbacks such as contact containment and manipulation of the blood sample, large and uncontrolled strain, and the inability to distinguish the contribution of elasticity and viscosity during blood coagulation. We developed a non-contact blood rheometer which uses a single drop of blood to measure its viscoelastic properties. Small sample size (typically 5-15 μL), low shear strain (linear viscoelasticity), and non-contact manipulation and containment of samples make this technique unique for real-time monitoring of blood coagulation. In the first part of this work, we addressed the development of the technique, benchmarking the results against known material properties standards. We observed large amplitude oscillations of the levitated drop results in multiple resonance modes and excessive dissipation. We suggested upper bound limits for drop oscillation amplitudes required to satisfy the Lamb theoretical expressions for drop frequency and damping. In the second part, we applied our technique to study sickle-cell disease. Our technique showed that the shape oscillation of blood drops was able to assess an abnormally increased viscosity in sickle cell patients when compared with normal controls over a range of hematocrit. Furthermore, the technique was sensitive enough to detect viscosity changes induced by hydroxyurea treatment. The third part of this work focused on blood coagulation monitoring. The technique showed sensitivity to coagulation parameters, such as platelet count, calcium ion concentration, and hematocrit. A comparison of the results with TEG showed coagulation started sooner in the levitation technique, but with a lower rate and lower maximum stiffness. Thus, the technique developed can be used as a monitoring tool to assess blood mechanical properties sensitively enough to be of use in clinical diagnostic settings.2020-06-04T00:00:00