Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition

The proper functioning of multicellular organisms requires the robust establishment of precise proportions between distinct cell-types. This developmental differentiation process typically involves intracellular regulatory and stochastic mechanisms to generate cell-fate diversity as well as intercellular mechanisms to coordinate cell-fate decisions at tissue level. We thus surmise that key insights about the developmental regulation of cell-type proportion can be captured by the modeling study of clustering dynamics in population of inhibitory-coupled noisy bistable systems. This general class of dynamical system is shown to exhibit a very stable two-cluster state, but also frustrated relaxation, collective oscillations or steady-state hopping which prevents from timely and reliably reaching a robust and well-proportioned clustered state. To circumvent these obstacles or to avoid fine-tuning, we highlight a general strategy based on dual-time positive feedback loops, such as mediated through transcriptional versus epigenetic mechanisms, which improves proportion regulation by coordinating early and flexible lineage priming with late and firm commitment. This result sheds new light on the respective and cooperative roles of multiple regulatory feedback, stochasticity and lateral inhibition in developmental dynamics

Multistable Decision Switches for Flexible Control of Epigenetic Differentiation

It is now recognized that molecular circuits with positive feedback can induce two different gene expression states (bistability) under the very same cellular conditions. Whether, and how, cells make use of the coexistence of a larger number of stable states (multistability) is however largely unknown. Here, we first examine how autoregulation, a common attribute of genetic master regulators, facilitates multistability in two-component circuits. A systematic exploration of these modules' parameter space reveals two classes of molecular switches, involving transitions in bistable (progression switches) or multistable (decision switches) regimes. We demonstrate the potential of decision switches for multifaceted stimulus processing, including strength, duration, and flexible discrimination. These tasks enhance response specificity, help to store short-term memories of recent signaling events, stabilize transient gene expression, and enable stochastic fate commitment. The relevance of these circuits is further supported by biological data, because we find them in numerous developmental scenarios. Indeed, many of the presented information-processing features of decision switches could ultimately demonstrate a more flexible control of epigenetic differentiation

A Structural Model for Fluctuations in Financial Markets

In this paper we provide a comprehensive analysis of a structural model for the dynamics of prices of assets traded in a market originally proposed in [1]. The model takes the form of an interacting generalization of the geometric Brownian motion model. It is formally equivalent to a model describing the stochastic dynamics of a system of analogue neurons, which is expected to exhibit glassy properties and thus many meta-stable states in a large portion of its parameter space. We perform a generating functional analysis, introducing a slow driving of the dynamics to mimic the effect of slowly varying macro-economic conditions. Distributions of asset returns over various time separations are evaluated analytically and are found to be fat-tailed in a manner broadly in line with empirical observations. Our model also allows to identify collective, interaction mediated properties of pricing distributions and it predicts pricing distributions which are significantly broader than their non-interacting counterparts, if interactions between prices in the model contain a ferro-magnetic bias. Using simulations, we are able to substantiate one of the main hypotheses underlying the original modelling, viz. that the phenomenon of volatility clustering can be rationalised in terms of an interplay between the dynamics within meta-stable states and the dynamics of occasional transitions between them.Comment: 16 pages, 8 (multi-part) figure

A Density-Dependent Switch Drives Stochastic Clustering and Polarization of Signaling Molecules

Positive feedback plays a key role in the ability of signaling molecules to form highly localized clusters in the membrane or cytosol of cells. Such clustering can occur in the absence of localizing mechanisms such as pre-existing spatial cues, diffusional barriers, or molecular cross-linking. What prevents positive feedback from amplifying inevitable biological noise when an un-clustered “off” state is desired? And, what limits the spread of clusters when an “on” state is desired? Here, we show that a minimal positive feedback circuit provides the general principle for both suppressing and amplifying noise: below a critical density of signaling molecules, clustering switches off; above this threshold, highly localized clusters are recurrently generated. Clustering occurs only in the stochastic regime, suggesting that finite sizes of molecular populations cannot be ignored in signal transduction networks. The emergence of a dominant cluster for finite numbers of molecules is partly a phenomenon of random sampling, analogous to the fixation or loss of neutral mutations in finite populations. We refer to our model as the “neutral drift polarity model.” Regulating the density of signaling molecules provides a simple mechanism for a positive feedback circuit to robustly switch between clustered and un-clustered states. The intrinsic ability of positive feedback both to create and suppress clustering is a general mechanism that could operate within diverse biological networks to create dynamic spatial organization

A Robust and Tunable Mitotic Oscillator in Artificial Cells

This dissertation aims to develop a droplet-based artificial cell system using cell-free extracts of Xenopus laevis eggs and understand mitotic oscillations with the proposed system. Single-cell analysis is pivotal to deciphering complex phenomena such as cellular heterogeneity, bistable switches, and oscillations, where a population ensemble cannot represent the individual behaviors. Despite having unique advantages of manipulation and characterization of biochemical networks, bulk cell-free systems lack the essential single-cell information to understand out-of-steady-state dynamics including cell cycles. In this dissertation, we present a novel artificial single-cell system for the study of mitotic dynamics by encapsulating Xenopus egg extracts in water-in-oil micro-emulsions. The artificial cells are different from real cells, i.e., their surface is formed by surfactant oil instead of the cell membrane. These “cells”, adjustable in sizes and periods, encapsulate cycling cytoplasmic extracts that can sustain mitotic oscillations for over 30 cycles. The artificial cells function in forms from the simplest cytoplasmic-only oscillators to the more complicated ones involving demembranated sperm chromatin that can reconstitute downstream mitotic events. The dynamic activities of cell cycle clock can be detected by fluorescent reporters such as cyclin B1-YFP and securin-mCherry. This innate flexibility makes it key to studying cell cycle clock tunability and stochasticity. Our experimental results indicate that the mitotic oscillators generated by our system are effectively tunable in frequency with cyclin B1 mRNAs and the dynamic behavior of single droplet oscillators is size-dependent. We also establish a stochastic model that highlights energy supply as an essential regulator of cell cycles. Moreover, the model explains experimental observations including the increase of baseline and amplitude of cyclin B1 time course. This dissertation study demonstrates a simple, powerful, and likely generalizable strategy of integrating single-cell approaches into conventional in vitro systems to study complex clock functions.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144115/1/yeguan_1.pd

The great societal transformations: epigenetic explorations: a transdisciplinary perspective on the evolution of modern knowledge societies ; part I, The Epigenetic Research Program (EPR) - basic building blocks ; part II, 'Great transformations' within modern societies - epigenetic transfer modules (TM)

'Die zwei Artikel in diesem Heft geben eine konzise Übersicht zu einer neuen, transdisziplinären Perspektive für die Analyse 'wissensbasierter Prozesse' innerhalb der unterschiedlichsten Bereiche in den Natur- und Sozialwissenschaften. Dieser neue Approach, der unter dem Namen 'epigenetisches Forschungsprogramm' (ERP) läuft, ermöglicht es, so die zentrale Botschaft dieses Reihenheftes, evolutionäre Entwicklungsmuster der 'sozialen Welt' - in ihren sozio-ökonomischen oder sozio-kulturellen Seiten - einzufangen und zu identifizieren. Dieses neuartige Leistungspotential erschließt sich durch den Aufbau eines konzeptionellen, theoretischen wie modellmäßigen Apparats von transdisziplinärem Geltungsbereich und durch die Differenzierung in zwei Ebenen, nämlich in einen theoretischen, modellbezogenen wie einen generellen anwendungsorientierten transdisziplinären Bereich und in Transfermodule sowie Datenfelder, welche einzelnen Disziplinfeldern zugeordnet werden können. Und hinsichtlich der Aufteilung der zwei Artikel offeriert der erste Teil eine Übersicht zu den einzelnen ERP-Bausteinen und der zweite Teil ein Set an 'Transfermodulen' speziell für die Analyse der Entwicklung moderner Gesellschaften und ihrer so vielfältig gewordenen und weit verteilten Wissensbasen.' (Autorenreferat)'The subsequent two parts give a precise overview of a new and transdisciplinary perspective for the study of 'knowledge based processes' in a wide variety of domains, including natural science fields and social science areas. The new approach which runs under the label of an 'epigenetic research program' (ERP) is able, so the core message, to capture the evolutionary development patterns of the socio-economic and the socio-cultural world. This achievement is brought about through the construction of a conceptual, theoretical and modeling apparatus of sufficient transdisciplinary generality and through the separation of two different levels, namely of ERP-meta-levels on the one hand and ERP-levels of application on the other hand. Meta-level elements are characterized, above all, by their transdisciplinary status, being not linked to any particular type of application domain, whereas building Blocks at application levels are clearly connected with special features in natural science or social science domains. With respect to the set of two consecutive articles, part I presents a general summary of the ERP-perspective and part II is devoted to a set of ERP 'transfer modules' mainly for the evolution of modern societies and their knowledge bases.' (author's abstract)

Studies of the Kinetics of Cell Cycle Processes in S. Cerevisiae: The Molecular Basis of Start Irreversibility and Cyclin-Cdk Ordering of Mitotic Events

The cell cycle machinery of Saccharomyces cerevisiae consists of a central negative feedback oscillator comprising cyclin-CDK and its antagonist, APCCdc20. This oscillator is stabilized and tuned by positive feedback loops, and its frequency is modulated by checkpoint controls. Either by directly triggering events, or by entraining independent oscillators controlling events, the cyclin-CDK oscillator regulates the key events of the cell cycle. These events have an established order and timing within the overall cycle. The work I describe in this thesis concerns two fundamental questions: how is the order and timing of cell cycle events controlled, and what sets the intrinsic frequency of the cell cycle oscillator? I describe work on two major processes in the cell division cycle that reveals two very different modes of regulation. The first of these processes – Start – represents a pivotal commitment to divide. In collaboration with Gilles Charvin, I demonstrate that positive feedback in the molecular machinery underlying Start acts as a bistable switch that renders this regulatory transition irreversible. The second major process is Mitosis, a set of events all triggered by the same class of cyclin-CDKs and yet occurring in a set and reproducible order. I describe an ordering mechanism underlying this choreography that relies on the natural ramping-up of cyclin-CDK activity level. The observation that different events require different levels of cyclin-CDK activity leads to the question of how these thresholds are set. To begin to answer this, I discuss how mitotic cyclin-CDK triggers two different events – depolarization of growth and formation of the mitotic spindle – in two very different ways. The first relies on entrainment of an independent oscillator controlling growth polarization; the other may involve the simultaneous regulation of multiple targets. The observation that cyclin-CDK is rate-limiting for mitotic events suggests that increasing the level of this key cell cycle regulator above its endogenous range should accelerate Mitosis, and I show evidence that this is the case. Quite surprisingly, this increase in cyclin-CDK abundance also accelerates the frequency of the cell cycle oscillator as a whole through its effect on growth. This provides an intriguing new answer to the question of what sets the intrinsic frequency of the cell cycle oscillator. Together, this work underscores the central role of the mitotic cyclin-CDK regulator, which controls not only the relative timing of individual cell cycle events, but also the growth rate of the cell, and the overall frequency of the cell cycle oscillator

A moonlighting enzyme imposes second messenger bistability to drive lifestyle decisions in E. coli.

Bacteria preferentially colonize surfaces and air-liquid interfaces as matrix embedded communities called biofilms. Biofilms exhibit specific physiological properties, including general stress tolerance, increased antibiotic recalcitrance and tolerance against phagocytic clearance. Together this largely accounts for increased biofilm persistence, chronic infections and infection relapses. One of the principle regulators of biofilm formation is c-di-GMP, a bacterial second messenger controlling various cellular processes. Cellular levels of c-di-GMP are controlled by two antagonistic enzyme families, diguanylate cyclases and phosphodiesterases. But despite the identification and characterization of an increasing number of components of the c-di-GMP network in different bacterial model organisms, details of c-di- GMP mediated decision-making have remained unclear. In particular, how cells shuttle between specific c-di-GMP regimes at the population and single cell level is largely unknown and moreover how these transitions are deterministically made in time and space, given that bacterial networks of diguanylate cyclases and phosphodiesterases show a high degree of complexity. Here we describe a novel mechanism regulating c-di-GMP mediated biofilm formation in E. coli. This mechanism relies on the bistable expression of a key phosphodiesterase that acts both as catalyst for c- di-GMP degradation and as a transcription factor promoting its own production. Bistability results from two interconnected positive feedback loops operating on the catalytic and gene expression level. Based on genetic, structural and biochemical analyses we postulate a simple substrate-induced switch mechanism through which this enzyme can sense changing concentration of c-di-GMP and convert this information into a bistable c-di-GMP response. This mechanism may explain how cellular heterogeneity of small signaling molecules is generated in bacteria and used as a bet hedging strategy for important lifestyle transitions