204 research outputs found

    Metabolite essentiality elucidates robustness of Escherichia coli metabolism

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    Complex biological systems are very robust to genetic and environmental changes at all levels of organization. Many biological functions of Escherichia coli metabolism can be sustained against single-gene or even multiple-gene mutations by using redundant or alternative pathways. Thus, only a limited number of genes have been identified to be lethal to the cell. In this regard, the reaction-centric gene deletion study has a limitation in understanding the metabolic robustness. Here, we report the use of flux-sum, which is the summation of all incoming or outgoing fluxes around a particular metabolite under pseudo-steady state conditions, as a good conserved property for elucidating such robustness of E. coli from the metabolite point of view. The functional behavior, as well as the structural and evolutionary properties of metabolites essential to the cell survival, was investigated by means of a constraints-based flux analysis under perturbed conditions. The essential metabolites are capable of maintaining a steady flux-sum even against severe perturbation by actively redistributing the relevant fluxes. Disrupting the flux-sum maintenance was found to suppress cell growth. This approach of analyzing metabolite essentiality provides insight into cellular robustness and concomitant fragility, which can be used for several applications, including the development of new drugs for treating pathogens.Comment: Supplements available at http://stat.kaist.ac.kr/publication/2007/PJKim_pnas_supplement.pd

    Shape, Size, and Robustness: Feasible Regions in the Parameter Space of Biochemical Networks

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    The concept of robustness of regulatory networks has received much attention in the last decade. One measure of robustness has been associated with the volume of the feasible region, namely, the region in the parameter space in which the system is functional. In this paper, we show that, in addition to volume, the geometry of this region has important consequences for the robustness and the fragility of a network. We develop an approximation within which we could algebraically specify the feasible region. We analyze the segment polarity gene network to illustrate our approach. The study of random walks in the parameter space and how they exit the feasible region provide us with a rich perspective on the different modes of failure of this network model. In particular, we found that, between two alternative ways of activating Wingless, one is more robust than the other. Our method provides a more complete measure of robustness to parameter variation. As a general modeling strategy, our approach is an interesting alternative to Boolean representation of biochemical networks

    Biomechanics and the thermotolerance of development

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    Successful completion of development requires coordination of patterning events with morphogenetic movements. Environmental variability challenges this coordination. For example, developing organisms encounter varying environmental temperatures that can strongly influence developmental rates. We hypothesized that the mechanics of morphogenesis would have to be finely adjusted to allow for normal morphogenesis across a wide range of developmental rates. We formulated our hypothesis as a simple model incorporating time-dependent application of force to a viscoelastic tissue. This model suggested that the capacity to maintain normal morphogenesis across a range of temperatures would depend on how both tissue viscoelasticity and the forces that drive deformation vary with temperature. To test this model we investigated how the mechanical behavior of embryonic tissue (Xenopus laevis) changed with temperature; we used a combination of micropipette aspiration to measure viscoelasticity, electrically induced contractions to measure cellular force generation, and confocal microscopy to measure endogenous contractility. Contrary to expectations, the viscoelasticity of the tissues and peak contractile tension proved invariant with temperature even as rates of force generation and gastrulation movements varied three-fold. Furthermore, the relative rates of different gastrulation movements varied with temperature: the speed of blastopore closure increased more slowly with temperature than the speed of the dorsal-to-ventral progression of involution. The changes in the relative rates of different tissue movements can be explained by the viscoelastic deformation model given observed viscoelastic properties, but only if morphogenetic forces increase slowly rather than all at once. © 2014 von Dassow et al

    Strength in numbers : collaborative science for new experimental model systems

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    The work is made available under the Creative Commons CCO public domain dedication.. The definitive version was published in PLoS Biology 16 (2018): e2006333, doi:10.1371/journal.pbio.2006333.Our current understanding of biology is heavily based on a small number of genetically tractable model organisms. Most eukaryotic phyla lack such experimental models, and this limits our ability to explore the molecular mechanisms that ultimately define their biology, ecology, and diversity. In particular, marine protists suffer from a paucity of model organisms despite playing critical roles in global nutrient cycles, food webs, and climate. To address this deficit, an initiative was launched in 2015 to foster the development of ecologically and taxonomically diverse marine protist genetic models. The development of new models faces many barriers, some technical and others institutional, and this often discourages the risky, long-term effort that may be required. To lower these barriers and tackle the complexity of this effort, a highly collaborative community-based approach was taken. Herein, we describe this approach, the advances achieved, and the lessons learned by participants in this novel community-based model for research.The research efforts, connections, and collaborations described in this paper and protocols.io (https://www.protocols.io/) were supported by the Gordon and Betty Moore Foundation’s Marine Microbiology Initiative

    Amplified biochemical oscillations in cellular systems

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    We describe a mechanism for pronounced biochemical oscillations, relevant to microscopic systems, such as the intracellular environment. This mechanism operates for reaction schemes which, when modeled using deterministic rate equations, fail to exhibit oscillations for any values of rate constants. The mechanism relies on amplification of the underlying stochasticity of reaction kinetics within a narrow window of frequencies. This amplification allows fluctuations to beat the central limit theorem, having a dominant effect even though the number of molecules in the system is relatively large. The mechanism is quantitatively studied within simple models of self-regulatory gene expression, and glycolytic oscillations.Comment: 35 pages, 6 figure

    Specialization Can Drive the Evolution of Modularity

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    Organismal development and many cell biological processes are organized in a modular fashion, where regulatory molecules form groups with many interactions within a group and few interactions between groups. Thus, the activity of elements within a module depends little on elements outside of it. Modularity facilitates the production of heritable variation and of evolutionary innovations. There is no consensus on how modularity might evolve, especially for modules in development. We show that modularity can increase in gene regulatory networks as a byproduct of specialization in gene activity. Such specialization occurs after gene regulatory networks are selected to produce new gene activity patterns that appear in a specific body structure or under a specific environmental condition. Modules that arise after specialization in gene activity comprise genes that show concerted changes in gene activities. This and other observations suggest that modularity evolves because it decreases interference between different groups of genes. Our work can explain the appearance and maintenance of modularity through a mechanism that is not contingent on environmental change. We also show how modularity can facilitate co-option, the utilization of existing gene activity to build new gene activity patterns, a frequent feature of evolutionary innovations

    Surprisingly Simple Mechanical Behavior of a Complex Embryonic Tissue

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    Background: Previous studies suggest that mechanical feedback could coordinate morphogenetic events in embryos. Furthermore, embryonic tissues have complex structure and composition and undergo large deformations during morphogenesis. Hence we expect highly non-linear and loading-rate dependent tissue mechanical properties in embryos. Methodology/Principal Findings: We used micro-aspiration to test whether a simple linear viscoelastic model was sufficient to describe the mechanical behavior of gastrula stage Xenopus laevis embryonic tissue in vivo. We tested whether these embryonic tissues change their mechanical properties in response to mechanical stimuli but found no evidence of changes in the viscoelastic properties of the tissue in response to stress or stress application rate. We used this model to test hypotheses about the pattern of force generation during electrically induced tissue contractions. The dependence of contractions on suction pressure was most consistent with apical tension, and was inconsistent with isotropic contraction. Finally, stiffer clutches generated stronger contractions, suggesting that force generation and stiffness may be coupled in the embryo. Conclusions/Significance: The mechanical behavior of a complex, active embryonic tissue can be surprisingly well described by a simple linear viscoelastic model with power law creep compliance, even at high deformations. We found no evidence of mechanical feedback in this system. Together these results show that very simple mechanical models can be useful in describing embryo mechanics. © 2010 von Dassow et al

    Aristotelian Essentialism: Essence in the Age of Evolution

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    The advent of contemporary evolutionary theory ushered in the eventual decline of Aristotelian Essentialism (Æ) – for it is widely assumed that essence does not, and cannot have any proper place in the age of evolution. This paper argues that this assumption is a mistake: if Æ can be suitably evolved, it need not face extinction. In it, I claim that if that theory’s fundamental ontology consists of dispositional properties, and if its characteristic metaphysical machinery is interpreted within the framework of contemporary evolutionary developmental biology, an evolved essentialism is available. The reformulated theory of Æ offered in this paper not only fails to fall prey to the typical collection of criticisms, but is also independently both theoretically and empirically plausible. The paper contends that, properly understood, essence belongs in the age of evolution

    The emerging structure of the Extended Evolutionary Synthesis: where does Evo-Devo fit in?

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    The Extended Evolutionary Synthesis (EES) debate is gaining ground in contemporary evolutionary biology. In parallel, a number of philosophical standpoints have emerged in an attempt to clarify what exactly is represented by the EES. For Massimo Pigliucci, we are in the wake of the newest instantiation of a persisting Kuhnian paradigm; in contrast, Telmo Pievani has contended that the transition to an EES could be best represented as a progressive reformation of a prior Lakatosian scientific research program, with the extension of its Neo-Darwinian core and the addition of a brand-new protective belt of assumptions and auxiliary hypotheses. Here, we argue that those philosophical vantage points are not the only ways to interpret what current proposals to ‘extend’ the Modern Synthesis-derived ‘standard evolutionary theory’ (SET) entail in terms of theoretical change in evolutionary biology. We specifically propose the image of the emergent EES as a vast network of models and interweaved representations that, instantiated in diverse practices, are connected and related in multiple ways. Under that assumption, the EES could be articulated around a paraconsistent network of evolutionary theories (including some elements of the SET), as well as models, practices and representation systems of contemporary evolutionary biology, with edges and nodes that change their position and centrality as a consequence of the co-construction and stabilization of facts and historical discussions revolving around the epistemic goals of this area of the life sciences. We then critically examine the purported structure of the EES—published by Laland and collaborators in 2015—in light of our own network-based proposal. Finally, we consider which epistemic units of Evo-Devo are present or still missing from the EES, in preparation for further analyses of the topic of explanatory integration in this conceptual framework

    Analysis of feedback loops and robustness in network evolution based on Boolean models

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    <p>Abstract</p> <p>Background</p> <p>Many biological networks such as protein-protein interaction networks, signaling networks, and metabolic networks have topological characteristics of a scale-free degree distribution. Preferential attachment has been considered as the most plausible evolutionary growth model to explain this topological property. Although various studies have been undertaken to investigate the structural characteristics of a network obtained using this growth model, its dynamical characteristics have received relatively less attention.</p> <p>Results</p> <p>In this paper, we focus on the robustness of a network that is acquired during its evolutionary process. Through simulations using Boolean network models, we found that preferential attachment increases the number of coupled feedback loops in the course of network evolution. Whereas, if networks evolve to have more coupled feedback loops rather than following preferential attachment, the resulting networks are more robust than those obtained through preferential attachment, although both of them have similar degree distributions.</p> <p>Conclusion</p> <p>The presented analysis demonstrates that coupled feedback loops may play an important role in network evolution to acquire robustness. The result also provides a hint as to why various biological networks have evolved to contain a number of coupled feedback loops.</p
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