Tissue organization by cadherin adhesion molecules: dynamic molecular and cellular mechanisms of morphogenetic regulation

PubMed Central

Niessen, Carien M.; Leckband, Deborah; Yap, Alpha S.

2013-01-01

This review addresses the cellular and molecular mechanisms of cadherin-based tissue morphogenesis. Tissue physiology is profoundly influenced by the distinctive organizations of cells in organs and tissues. In metazoa, adhesion receptors of the classical cadherin family play important roles in establishing and maintaining such tissue organization. Indeed, it is apparent that cadherins participate in a range of morphogenetic events that range from support of tissue integrity to dynamic cellular rearrangements. A comprehensive understanding of cadherin-based morphogenesis must then define the molecular and cellular mechanisms that support these distinct cadherin biologies. Here we focus on four key mechanistic elements: the molecular basis for adhesion through cadherin ectodomains; the regulation of cadherin expression at the cell surface; cooperation between cadherins and the actin cytoskeleton; and regulation by cell signaling. We discuss current progress and outline issues for further research in these fields. PMID:21527735

Exploration of cellular reaction systems.

PubMed

Kirkilionis, Markus

2010-01-01

We discuss and review different ways to map cellular components and their temporal interaction with other such components to different non-spatially explicit mathematical models. The essential choices made in the literature are between discrete and continuous state spaces, between rule and event-based state updates and between deterministic and stochastic series of such updates. The temporal modelling of cellular regulatory networks (dynamic network theory) is compared with static network approaches in two first introductory sections on general network modelling. We concentrate next on deterministic rate-based dynamic regulatory networks and their derivation. In the derivation, we include methods from multiscale analysis and also look at structured large particles, here called macromolecular machines. It is clear that mass-action systems and their derivatives, i.e. networks based on enzyme kinetics, play the most dominant role in the literature. The tools to analyse cellular reaction networks are without doubt most complete for mass-action systems. We devote a long section at the end of the review to make a comprehensive review of related tools and mathematical methods. The emphasis is to show how cellular reaction networks can be analysed with the help of different associated graphs and the dissection into modules, i.e. sub-networks.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Virtual Embryo: Cell-Agent Based Modeling of Developmental Processes and Toxicities (CSS BOSC)

EPA Science Inventory

Spatial regulation of cellular dynamics is fundamental to morphological development. As such, chemical disruption of spatial dynamics is a determinant of developmental toxicity. Incorporating spatial dynamics into AOPs for developmental toxicity is desired but constrained by the ...

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

PubMed

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling. Agent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM.

PubMed

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2015-07-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location.

Cellular dynamics in the muscle satellite cell niche

PubMed Central

Bentzinger, C Florian; Wang, Yu Xin; Dumont, Nicolas A; Rudnicki, Michael A

2013-01-01

Satellite cells, the quintessential skeletal muscle stem cells, reside in a specialized local environment whose anatomy changes dynamically during tissue regeneration. The plasticity of this niche is attributable to regulation by the stem cells themselves and to a multitude of functionally diverse cell types. In particular, immune cells, fibrogenic cells, vessel-associated cells and committed and differentiated cells of the myogenic lineage have emerged as important constituents of the satellite cell niche. Here, we discuss the cellular dynamics during muscle regeneration and how disease can lead to perturbation of these mechanisms. To define the role of cellular components in the muscle stem cell niche is imperative for the development of cell-based therapies, as well as to better understand the pathobiology of degenerative conditions of the skeletal musculature. PMID:24232182

Dynamic Simulation of 1D Cellular Automata in the Active aTAM

PubMed Central

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2016-01-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location. PMID:27789918

Simulation of Healing Threshold in Strain-Induced Inflammation Through a Discrete Informatics Model.

PubMed

Ibrahim, Israr Bin M; Sarma O V, Sanjay; Pidaparti, Ramana M

2018-05-01

Respiratory diseases such as asthma and acute respiratory distress syndrome as well as acute lung injury involve inflammation at the cellular level. The inflammation process is very complex and is characterized by the emergence of cytokines along with other changes in cellular processes. Due to the complexity of the various constituents that makes up the inflammation dynamics, it is necessary to develop models that can complement experiments to fully understand inflammatory diseases. In this study, we developed a discrete informatics model based on cellular automata (CA) approach to investigate the influence of elastic field (stretch/strain) on the dynamics of inflammation and account for probabilistic adaptation based on statistical interpretation of existing experimental data. Our simulation model investigated the effects of low, medium, and high strain conditions on inflammation dynamics. Results suggest that the model is able to indicate the threshold of innate healing of tissue as a response to strain experienced by the tissue. When strain is under the threshold, the tissue is still capable of adapting its structure to heal the damaged part. However, there exists a strain threshold where healing capability breaks down. The results obtained demonstrate that the developed discrete informatics based CA model is capable of modeling and giving insights into inflammation dynamics parameters under various mechanical strain/stretch environments.

Under the Microscope: Single-Domain Antibodies for Live-Cell Imaging and Super-Resolution Microscopy.

PubMed

Traenkle, Bjoern; Rothbauer, Ulrich

2017-01-01

Single-domain antibodies (sdAbs) have substantially expanded the possibilities of advanced cellular imaging such as live-cell or super-resolution microscopy to visualize cellular antigens and their dynamics. In addition to their unique properties including small size, high stability, and solubility in many environments, sdAbs can be efficiently functionalized according to the needs of the respective imaging approach. Genetically encoded intrabodies fused to fluorescent proteins (chromobodies) have become versatile tools to study dynamics of endogenous proteins in living cells. Additionally, sdAbs conjugated to organic dyes were shown to label cellular structures with high density and minimal fluorophore displacement making them highly attractive probes for super-resolution microscopy. Here, we review recent advances of the chromobody technology to visualize localization and dynamics of cellular targets and the application of chromobody-based cell models for compound screening. Acknowledging the emerging importance of super-resolution microscopy in cell biology, we further discuss advantages and challenges of sdAbs for this technology.

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment. PMID:29303160

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamic behavior of cellular materials and cellular structures: Experiments and modeling

NASA Astrophysics Data System (ADS)

Gao, Ziyang

Cellular solids, including cellular materials and cellular structures (CMS), have attracted people's great interests because of their low densities and novel physical, mechanical, thermal, electrical and acoustic properties. They offer potential for lightweight structures, energy absorption, thermal management, etc. Therefore, the studies of cellular solids have become one of the hottest research fields nowadays. From energy absorption point of view, any plastically deformed structures can be divided into two types (called type I and type II), and the basic cells of the CMS may take the configurations of these two types of structures. Accordingly, separated discussions are presented in this thesis. First, a modified 1-D model is proposed and numerically solved for a typical type II structure. Good agreement is achieved with the previous experimental data, hence is used to simulate the dynamic behavior of a type II chain. Resulted from different load speeds, interesting collapse modes are observed, and the parameters which govern the cell's post-collapse behavior are identified through a comprehensive non-dimensional analysis on general cellular chains. Secondly, the MHS specimens are chosen as an example of type I foam materials because of their good uniformity of the cell geometry. An extensive experimental study was carried out, where more attention was paid to their responses to dynamic loadings. Great enhancement of the stress-strain curve was observed in dynamic cases, and the energy absorption capacity is found to be several times higher than that of the commercial metal foams. Based on the experimental study, finite elemental simulations and theoretical modeling are also conducted, achieving good agreements and demonstrating the validities of those models. It is believed that the experimental, numerical and analytical results obtained in the present study will certainly deepen the understanding of the unsolved fundamental issues on the mechanical behavior of cellular solids and make substantial contributions to the theoretical advance of impact dynamics.

Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

PubMed Central

de la Fuente, Ildefonso Martínez

2010-01-01

One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways.

PubMed

Hardy, Simon; Robillard, Pierre N

2008-01-15

Cellular signaling networks are dynamic systems that propagate and process information, and, ultimately, cause phenotypical responses. Understanding the circuitry of the information flow in cells is one of the keys to understanding complex cellular processes. The development of computational quantitative models is a promising avenue for attaining this goal. Not only does the analysis of the simulation data based on the concentration variations of biological compounds yields information about systemic state changes, but it is also very helpful for obtaining information about the dynamics of signal propagation. This article introduces a new method for analyzing the dynamics of signal propagation in signaling pathways using Petri net theory. The method is demonstrated with the Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) regulation network. The results constitute temporal information about signal propagation in the network, a simplified graphical representation of the network and of the signal propagation dynamics and a characterization of some signaling routes as regulation motifs.

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

Generic framework for mining cellular automata models on protein-folding simulations.

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Modeling mechanical interactions in growing populations of rod-shaped bacteria

NASA Astrophysics Data System (ADS)

Winkle, James J.; Igoshin, Oleg A.; Bennett, Matthew R.; Josić, Krešimir; Ott, William

2017-10-01

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell’s environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Wavelet-based multiscale analysis of bioimpedance data measured by electric cell-substrate impedance sensing for classification of cancerous and normal cells.

PubMed

Das, Debanjan; Shiladitya, Kumar; Biswas, Karabi; Dutta, Pranab Kumar; Parekh, Aditya; Mandal, Mahitosh; Das, Soumen

2015-12-01

The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

PubMed

Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

2017-01-01

Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging.

PubMed

Held, Michael; Schmitz, Michael H A; Fischer, Bernd; Walter, Thomas; Neumann, Beate; Olma, Michael H; Peter, Matthias; Ellenberg, Jan; Gerlich, Daniel W

2010-09-01

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

Quantitative measurement of intracellular protein dynamics using photobleaching or photoactivation of fluorescent proteins.

PubMed

Matsuda, Tomoki; Nagai, Takeharu

2014-12-01

Unlike in vitro protein dynamics, intracellular protein dynamics are intricately regulated by protein-protein interactions or interactions between proteins and other cellular components, including nucleic acids, the plasma membrane and the cytoskeleton. Alteration of these dynamics plays a crucial role in physiological phenomena such as gene expression and cell division. Live-cell imaging via microscopy with the inherent properties of fluorescent proteins, i.e. photobleaching and photoconversion, or fluorescence correlation spectroscopy, provides insight into the movement of proteins and their interactions with cellular components. This article reviews techniques based on photo-induced changes in the physicochemical properties of fluorescent proteins to measure protein dynamics inside living cells, and it also discusses the strengths and weaknesses of these techniques. © The Author 2014. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Triangles bridge the scales: Quantifying cellular contributions to tissue deformation

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Etournay, Raphaël; Popović, Marko; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

2017-03-01

In this article, we propose a general framework to study the dynamics and topology of cellular networks that capture the geometry of cell packings in two-dimensional tissues. Such epithelia undergo large-scale deformation during morphogenesis of a multicellular organism. Large-scale deformations emerge from many individual cellular events such as cell shape changes, cell rearrangements, cell divisions, and cell extrusions. Using a triangle-based representation of cellular network geometry, we obtain an exact decomposition of large-scale material deformation. Interestingly, our approach reveals contributions of correlations between cellular rotations and elongation as well as cellular growth and elongation to tissue deformation. Using this triangle method, we discuss tissue remodeling in the developing pupal wing of the fly Drosophila melanogaster.

Micro- and nanoscale devices for investigation of epigenetics and chromatin dynamics

PubMed Central

2014-01-01

DNA is the blueprint upon which life is based and transmitted, yet the manner in which chromatin, the dynamic complex of nucleic acids and proteins, is packaged and behaves within the cellular nucleus has only begun to be investigated. The packaging and modifications around the genome have been shown to exert significant influence on cellular behaviour and in turn, human development and disease. However, conventional techniques for studying epigenetic or conformational modifications of chromosomes have inherent limitations, and therefore, new methods based on micro- and nanoscale devices have been sought. Here, we review the development of these devices and explore their use in the study of DNA and chromatin modifications and higher order chromatin structure. PMID:24091454

From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

PubMed

Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

2017-01-01

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The concept of self-organization in cellular architecture

PubMed Central

Misteli, Tom

2001-01-01

In vivo microscopy has recently revealed the dynamic nature of many cellular organelles. The dynamic properties of several cellular structures are consistent with a role for self-organization in their formation, maintenance, and function; therefore, self-organization might be a general principle in cellular organization. PMID:11604416

Tempo-spatially resolved cellular dynamics of human immunodeficiency virus transacting activator of transcription (Tat) peptide-modified nanocargos in living cells

NASA Astrophysics Data System (ADS)

Wei, Lin; Yang, Qiaoyu; Xiao, Lehui

2014-08-01

Understanding the cellular uptake mechanism and intracellular fate of nanocarriers in living cells is of great importance for the rational design of efficient drug delivery cargos as well as the development of robust biomedical diagnostic probes. In present study, with a dual wavelength view darkfield microscope (DWVD), the tempo-spatially resolved dynamics of Tat peptide-functionalized gold nanoparticles (TGNPs, with size similar to viruses) in living HeLa cells were extensively explored. It was found that energy-dependent endocytosis (both clathrin- and caveolae-mediated processes were involved) was the prevailing pathway for the cellular uptake of TGNPs. The time-correlated dynamic spatial distribution information revealed that TGNPs could not actively target the cell nuclei, which is contrary to previous observations based on fixed cell results. More importantly, the inheritance of TGNPs to the daughter cells through mitosis was found to be the major route to metabolize TGNPs by HeLa cells. These understandings on the cellular uptake mechanism and intracellular fate of nanocargos in living cells would provide deep insight on how to improve and controllably manipulate their translocation efficiency for targeted drug delivery.Understanding the cellular uptake mechanism and intracellular fate of nanocarriers in living cells is of great importance for the rational design of efficient drug delivery cargos as well as the development of robust biomedical diagnostic probes. In present study, with a dual wavelength view darkfield microscope (DWVD), the tempo-spatially resolved dynamics of Tat peptide-functionalized gold nanoparticles (TGNPs, with size similar to viruses) in living HeLa cells were extensively explored. It was found that energy-dependent endocytosis (both clathrin- and caveolae-mediated processes were involved) was the prevailing pathway for the cellular uptake of TGNPs. The time-correlated dynamic spatial distribution information revealed that TGNPs could not actively target the cell nuclei, which is contrary to previous observations based on fixed cell results. More importantly, the inheritance of TGNPs to the daughter cells through mitosis was found to be the major route to metabolize TGNPs by HeLa cells. These understandings on the cellular uptake mechanism and intracellular fate of nanocargos in living cells would provide deep insight on how to improve and controllably manipulate their translocation efficiency for targeted drug delivery. Electronic supplementary information (ESI) available: Experimental section and additional supporting results as noted in the text. See DOI: 10.1039/c4nr02732a

Dynamical and Mechanistic Reconstructive Approaches of T Lymphocyte Dynamics: Using Visual Modeling Languages to Bridge the Gap between Immunologists, Theoreticians, and Programmers

PubMed Central

Thomas-Vaslin, Véronique; Six, Adrien; Ganascia, Jean-Gabriel; Bersini, Hugues

2013-01-01

Dynamic modeling of lymphocyte behavior has primarily been based on populations based differential equations or on cellular agents moving in space and interacting each other. The final steps of this modeling effort are expressed in a code written in a programing language. On account of the complete lack of standardization of the different steps to proceed, we have to deplore poor communication and sharing between experimentalists, theoreticians and programmers. The adoption of diagrammatic visual computer language should however greatly help the immunologists to better communicate, to more easily identify the models similarities and facilitate the reuse and extension of existing software models. Since immunologists often conceptualize the dynamical evolution of immune systems in terms of “state-transitions” of biological objects, we promote the use of unified modeling language (UML) state-transition diagram. To demonstrate the feasibility of this approach, we present a UML refactoring of two published models on thymocyte differentiation. Originally built with different modeling strategies, a mathematical ordinary differential equation-based model and a cellular automata model, the two models are now in the same visual formalism and can be compared. PMID:24101919

Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells

PubMed Central

Chudasama, Vaishali L.; Ovacik, Meric A.; Abernethy, Darrell R.

2015-01-01

Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens. PMID:26163548

Phononic Band Gaps in 2D Quadratic and 3D Cubic Cellular Structures

PubMed Central

Warmuth, Franziska; Körner, Carolin

2015-01-01

The static and dynamic mechanical behaviour of cellular materials can be designed by the architecture of the underlying unit cell. In this paper, the phononic band structure of 2D and 3D cellular structures is investigated. It is shown how the geometry of the unit cell influences the band structure and eventually leads to full band gaps. The mechanism leading to full band gaps is elucidated. Based on this knowledge, a 3D cellular structure with a broad full band gap is identified. Furthermore, the dependence of the width of the gap on the geometry parameters of the unit cell is presented. PMID:28793713

Phononic Band Gaps in 2D Quadratic and 3D Cubic Cellular Structures.

PubMed

Warmuth, Franziska; Körner, Carolin

2015-12-02

The static and dynamic mechanical behaviour of cellular materials can be designed by the architecture of the underlying unit cell. In this paper, the phononic band structure of 2D and 3D cellular structures is investigated. It is shown how the geometry of the unit cell influences the band structure and eventually leads to full band gaps. The mechanism leading to full band gaps is elucidated. Based on this knowledge, a 3D cellular structure with a broad full band gap is identified. Furthermore, the dependence of the width of the gap on the geometry parameters of the unit cell is presented.

Texturing Silicon Nanowires for Highly Localized Optical Modulation of Cellular Dynamics.

PubMed

Fang, Yin; Jiang, Yuanwen; Acaron Ledesma, Hector; Yi, Jaeseok; Gao, Xiang; Weiss, Dara E; Shi, Fengyuan; Tian, Bozhi

2018-06-18

Engineered silicon-based materials can display photoelectric and photothermal responses under light illumination, which may lead to further innovations at the silicon-biology interfaces. Silicon nanowires have small radial dimensions, promising as highly localized cellular modulators, however the single crystalline form typically has limited photothermal efficacy due to the poor light absorption and fast heat dissipation. In this work, we report strategies to improve the photothermal response from silicon nanowires by introducing nanoscale textures on the surface and in the bulk. We next demonstrate high-resolution extracellular modulation of calcium dynamics in a number of mammalian cells including glial cells, neurons, and cancer cells. The new materials may be broadly used in probing and modulating electrical and chemical signals at the subcellular length scale, which is currently a challenge in the field of electrophysiology or cellular engineering.

Generation and precise control of dynamic biochemical gradients for cellular assays

NASA Astrophysics Data System (ADS)

Saka, Yasushi; MacPherson, Murray; Giuraniuc, Claudiu V.

2017-03-01

Spatial gradients of diffusible signalling molecules play crucial roles in controlling diverse cellular behaviour such as cell differentiation, tissue patterning and chemotaxis. In this paper, we report the design and testing of a microfluidic device for diffusion-based gradient generation for cellular assays. A unique channel design of the device eliminates cross-flow between the source and sink channels, thereby stabilizing gradients by passive diffusion. The platform also enables quick and flexible control of chemical concentration that makes highly dynamic gradients in diffusion chambers. A model with the first approximation of diffusion and surface adsorption of molecules recapitulates the experimentally observed gradients. Budding yeast cells cultured in a gradient of a chemical inducer expressed a reporter fluorescence protein in a concentration-dependent manner. This microfluidic platform serves as a versatile prototype applicable to a broad range of biomedical investigations.

Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

1997-04-01

The use of artificial neural networks (NNs) to address the channel assignment problem (CAP) for cellular time-division multiple access and code-division multiple access networks has previously been investigated by this author and many others. The investigations to date have been based on a hexagonal cell structure established by omnidirectional antennas at the base stations. No account was taken of the use of spatial isolation enabled by directional antennas to reduce interference between mobiles. Any reduction in interference translates into increased capacity and consequently alters the performance of the NNs. Previous studies have sought to improve the performance of Hopfield- Tank network algorithms and self-organizing feature map algorithms applied primarily to static channel assignment (SCA) for cellular networks that handle uniformly distributed, stationary traffic in each cell for a single type of service. The resulting algorithms minimize energy functions representing interference constraint and ad hoc conditions that promote convergence to optimal solutions. While the structures of the derived neural network algorithms (NNAs) offer the potential advantages of inherent parallelism and adaptability to changing system conditions, this potential has yet to be fulfilled the CAP for emerging mobile networks. The next-generation communication infrastructures must accommodate dynamic operating conditions. Macrocell topologies are being refined to microcells and picocells that can be dynamically sectored by adaptively controlled, directional antennas and programmable transceivers. These networks must support the time-varying demands for personal communication services (PCS) that simultaneously carry voice, data and video and, thus, require new dynamic channel assignment (DCA) algorithms. This paper examines the impact of dynamic cell sectoring and geometric conditioning on NNAs developed for SCA in omnicell networks with stationary traffic to improve the metrics of convergence rate and call blocking. Genetic algorithms (GAs) are also considered in PCS networks as a means to overcome the known weakness of Hopfield NNAs in determining global minima. The resulting GAs for DCA in PCS networks are compared to improved DCA algorithms based on Hopfield NNs for stationary cellular networks. Algorithm performance is compared on the basis of rate of convergence, blocking probability, analytic complexity, and parametric sensitivity to transient traffic demands and channel interference.

Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

PubMed

Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

2008-09-09

Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and energetics in skeletal muscle during physiological stresses such as ischemia, hypoxia, and exercise.

ReaDDy - A Software for Particle-Based Reaction-Diffusion Dynamics in Crowded Cellular Environments

PubMed Central

Schöneberg, Johannes; Noé, Frank

2013-01-01

We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics. PMID:24040218

Dynamic analysis of CO₂ labeling and cell respiration using membrane-inlet mass spectrometry.

PubMed

Yang, Tae Hoon

2014-01-01

Here, we introduce a mass spectrometry-based analytical method and relevant technical details for dynamic cell respiration and CO2 labeling analysis. Such measurements can be utilized as additional information and constraints for model-based (13)C metabolic flux analysis. Dissolved dynamics of oxygen consumption and CO2 mass isotopomer evolution from (13)C-labeled tracer substrates through different cellular processes can be precisely measured on-line using a miniaturized reactor system equipped with a membrane-inlet mass spectrometer. The corresponding specific rates of physiologically relevant gases and CO2 mass isotopomers can be quantified within a short-term range based on the liquid-phase dynamics of dissolved fermentation gases.

A fuzzy-theory-based behavioral model for studying pedestrian evacuation from a single-exit room

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lo, Siuming

2016-08-01

Many mass events in recent years have highlighted the importance of research on pedestrian evacuation dynamics. A number of models have been developed to analyze crowd behavior under evacuation situations. However, few focus on pedestrians' decision-making with respect to uncertainty, vagueness and imprecision. In this paper, a discrete evacuation model defined on the cellular space is proposed according to the fuzzy theory which is able to describe imprecise and subjective information. Pedestrians' percept information and various characteristics are regarded as fuzzy input. Then fuzzy inference systems with rule bases, which resemble human reasoning, are established to obtain fuzzy output that decides pedestrians' movement direction. This model is tested in two scenarios, namely in a single-exit room with and without obstacles. Simulation results reproduce some classic dynamics phenomena discovered in real building evacuation situations, and are consistent with those in other models and experiments. It is hoped that this study will enrich movement rules and approaches in traditional cellular automaton models for evacuation dynamics.

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

Computer simulation studies on passive recruitment dynamics of lipids induced by the adsorption of charged nanoparticles.

PubMed

Li, Yang

2014-07-07

The recruitment dynamics of lipids in the biomembrane is believed to play an important role in a variety of cellular processes. In this work, we investigate the nanoparticle-induced recruitment dynamics of lipids in the heterogeneous phospholipid bilayers of distearoyl-phosphatidylcholine (DSPC) and dioleoyl-phosphatidylglycerol (DOPG) via coarse-grained molecular dynamics simulations. Three dynamic modes of individual charged DOPG lipid molecules have been taken into account in the recruitment process: lateral diffusion, protrusions, and flip-flops. Based on analysis of the mobility pattern of lipids, structural variations in the membrane as well as activation energy of the structure of lipid eyelids characterized by the potential of mean force, we have concluded that the electrostatic attraction of nanoparticles plays a crucial role in the recruitment process of lipids in phospholipid bilayers. These studies are consistent with experimental observations and to some extent give insight into the origin of some cellular processes such as signaling, formation of lipid rafts, and endocytosis.

Cytoskeletal self-organization in neuromorphogenesis.

PubMed

Dehmelt, Leif

2014-01-01

Self-organization of dynamic microtubules via interactions with associated motors plays a critical role in spindle formation. The microtubule-based mechanisms underlying other aspects of cellular morphogenesis, such as the formation and development of protrusions from neuronal cells is less well understood. In a recent study, we investigated the molecular mechanism that underlies the massive reorganization of microtubules induced in non-neuronal cells by expression of the neuronal microtubule stabilizer MAP2c. In that study we directly observed cortical dynein complexes and how they affect the dynamic behavior of motile microtubules in living cells. We found that stationary dynein complexes transiently associate with motile microtubules near the cell cortex and that their rapid turnover facilitates efficient microtubule transport. Here, we discuss our findings in the larger context of cellular morphogenesis with specific focus on self-organizing principles from which cellular shape patterns such as the thin protrusions of neurons can emerge.

Cytoskeletal self-organization in neuromorphogenesis

PubMed Central

Dehmelt, Leif

2014-01-01

Self-organization of dynamic microtubules via interactions with associated motors plays a critical role in spindle formation. The microtubule-based mechanisms underlying other aspects of cellular morphogenesis, such as the formation and development of protrusions from neuronal cells is less well understood. In a recent study, we investigated the molecular mechanism that underlies the massive reorganization of microtubules induced in non-neuronal cells by expression of the neuronal microtubule stabilizer MAP2c. In that study we directly observed cortical dynein complexes and how they affect the dynamic behavior of motile microtubules in living cells. We found that stationary dynein complexes transiently associate with motile microtubules near the cell cortex and that their rapid turnover facilitates efficient microtubule transport. Here, we discuss our findings in the larger context of cellular morphogenesis with specific focus on self-organizing principles from which cellular shape patterns such as the thin protrusions of neurons can emerge. PMID:24847718

Quantitation of Cellular Dynamics in Growing Arabidopsis Roots with Light Sheet Microscopy

PubMed Central

Birnbaum, Kenneth D.; Leibler, Stanislas

2011-01-01

To understand dynamic developmental processes, living tissues have to be imaged frequently and for extended periods of time. Root development is extensively studied at cellular resolution to understand basic mechanisms underlying pattern formation and maintenance in plants. Unfortunately, ensuring continuous specimen access, while preserving physiological conditions and preventing photo-damage, poses major barriers to measurements of cellular dynamics in growing organs such as plant roots. We present a system that integrates optical sectioning through light sheet fluorescence microscopy with hydroponic culture that enables us to image, at cellular resolution, a vertically growing Arabidopsis root every few minutes and for several consecutive days. We describe novel automated routines to track the root tip as it grows, to track cellular nuclei and to identify cell divisions. We demonstrate the system's capabilities by collecting data on divisions and nuclear dynamics. PMID:21731697

A Compact Synchronous Cellular Model of Nonlinear Calcium Dynamics: Simulation and FPGA Synthesis Results.

PubMed

Soleimani, Hamid; Drakakis, Emmanuel M

2017-06-01

Recent studies have demonstrated that calcium is a widespread intracellular ion that controls a wide range of temporal dynamics in the mammalian body. The simulation and validation of such studies using experimental data would benefit from a fast large scale simulation and modelling tool. This paper presents a compact and fully reconfigurable cellular calcium model capable of mimicking Hopf bifurcation phenomenon and various nonlinear responses of the biological calcium dynamics. The proposed cellular model is synthesized on a digital platform for a single unit and a network model. Hardware synthesis, physical implementation on FPGA, and theoretical analysis confirm that the proposed cellular model can mimic the biological calcium behaviors with considerably low hardware overhead. The approach has the potential to speed up large-scale simulations of slow intracellular dynamics by sharing more cellular units in real-time. To this end, various networks constructed by pipelining 10 k to 40 k cellular calcium units are compared with an equivalent simulation run on a standard PC workstation. Results show that the cellular hardware model is, on average, 83 times faster than the CPU version.

Micro- and nanoscale devices for the investigation of epigenetics and chromatin dynamics

NASA Astrophysics Data System (ADS)

Aguilar, Carlos A.; Craighead, Harold G.

2013-10-01

Deoxyribonucleic acid (DNA) is the blueprint on which life is based and transmitted, but the way in which chromatin -- a dynamic complex of nucleic acids and proteins -- is packaged and behaves in the cellular nucleus has only begun to be investigated. Epigenetic modifications sit 'on top of' the genome and affect how DNA is compacted into chromatin and transcribed into ribonucleic acid (RNA). The packaging and modifications around the genome have been shown to exert significant influence on cellular behaviour and, in turn, human development and disease. However, conventional techniques for studying epigenetic or conformational modifications of chromosomes have inherent limitations and, therefore, new methods based on micro- and nanoscale devices have been sought. Here, we review the development of these devices and explore their use in the study of DNA modifications, chromatin modifications and higher-order chromatin structures.

Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

NASA Astrophysics Data System (ADS)

Xia, Weiwei; Shen, Lianfeng

We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Dynamic intervention: pathogen disarmament of mitochondrial-based immune surveillance.

PubMed

Holland, Robin L; Blanke, Steven R

2014-11-12

In this issue of Cell Host & Microbe, Suzuki et al. (2014) describe a Vibrio cholerae Type-III-secreted effector that targets mitochondrial dynamics to dampen host innate immune signaling. This suggests that mammalian hosts possess surveillance mechanisms to monitor pathogen-mediated alterations in the integrity of normal cellular processes and organelles. Copyright © 2014 Elsevier Inc. All rights reserved.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Space-time dynamics of Stem Cell Niches: a unified approach for Plants.

PubMed

Pérez, Maria Del Carmen; López, Alejandro; Padilla, Pablo

2013-06-01

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Space-time dynamics of stem cell niches: a unified approach for plants.

PubMed

Pérez, Maria del Carmen; López, Alejandro; Padilla, Pablo

2013-04-02

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.

Discrete Dynamics Lab

NASA Astrophysics Data System (ADS)

Wuensche, Andrew

DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.

Impact of jamming on collective cell migration

NASA Astrophysics Data System (ADS)

Nnetu, Kenechukwu David; Knorr, Melanie; Pawlizak, Steve; Fuhs, Thomas; Zink, Mareike; KäS, Josef A.

2012-02-01

Multi-cellular migration plays an important role in physiological processes such as embryogenesis, cancer metastasis and tissue repair. During migration, single cells undergo cycles of extension, adhesion and retraction resulting in morphological changes. In a confluent monolayer, there are inter-cellular interactions and crowding, however, the impact of these interactions on the dynamics and elasticity of the monolayer at the multi-cellular and single cell level is not well understood. Here we study the dynamics of a confluent epithelial monolayer by simultaneously measuring cell motion at the multi-cellular and single cell level for various cell densities and tensile elasticity. At the multi-cellular level, the system exhibited spatial kinetic transitions from isotropic to anisotropic migration on long times and the velocity of the monolayer decreased with increasing cell density. Moreover, the dynamics was spatially and temporally heterogeneous. Interestingly, the dynamics was also heterogeneous in wound-healing assays and the correlation length was fitted by compressed exponential. On the single cell scale, we observed transient caging effects with increasing cage rearrangement times as the system age due to an increase in density. Also, the density dependent elastic modulus of the monolayer scaled as a weak power law. Together, these findings suggest that caging effects at the single cell level initiates a slow and heterogeneous dynamics at the multi-cellular level which is similar to the glassy dynamics of deformable colloidal systems.

Strange non-chaotic attractors in a state controlled-cellular neural network-based quasiperiodically forced MLC circuit

NASA Astrophysics Data System (ADS)

Ezhilarasu, P. Megavarna; Inbavalli, M.; Murali, K.; Thamilmaran, K.

2018-07-01

In this paper, we report the dynamical transitions to strange non-chaotic attractors in a quasiperiodically forced state controlled-cellular neural network (SC-CNN)-based MLC circuit via two different mechanisms, namely the Heagy-Hammel route and the gradual fractalisation route. These transitions were observed through numerical simulations and hardware experiments and confirmed using statistical tools, such as maximal Lyapunov exponent spectrum and its variance and singular continuous spectral analysis. We find that there is a remarkable agreement of the results from both numerical simulations as well as from hardware experiments.

Open-Cellular Co-Base and Ni-Base Superalloys Fabricated by Electron Beam Melting

PubMed Central

Murr, Lawrence; Li, Shujun; Tian, Yuxing; Amato, Krista; Martinez, Edwin; Medina, Frank

2011-01-01

Reticulated mesh samples of Co-29Cr-6Mo alloy and Ni-21Cr-9Mo-4Nb alloy (625) and stochastic foam samples of Co-29Cr-6Mo alloy fabricated by electron beam melting were characterized by optical metallography, and the dynamic stiffness (Young’s modulus) was measured by resonant frequency analysis. The relative stiffness (E/Es) versus relative density (ρ/ρs) plotted on a log-log basis resulted in a fitted straight line with a slope n ≅ 2, consistent with that for ideal open cellular materials. PMID:28879949

Definition and application of a five-parameter characterization of one-dimensional cellular automata rule space.

PubMed

Oliveira, G M; de Oliveira, P P; Omar, N

2001-01-01

Cellular automata (CA) are important as prototypical, spatially extended, discrete dynamical systems. Because the problem of forecasting dynamic behavior of CA is undecidable, various parameter-based approximations have been developed to address the problem. Out of the analysis of the most important parameters available to this end we proposed some guidelines that should be followed when defining a parameter of that kind. Based upon the guidelines, new parameters were proposed and a set of five parameters was selected; two of them were drawn from the literature and three are new ones, defined here. This article presents all of them and makes their qualities evident. Then, two results are described, related to the use of the parameter set in the Elementary Rule Space: a phase transition diagram, and some general heuristics for forecasting the dynamics of one-dimensional CA. Finally, as an example of the application of the selected parameters in high cardinality spaces, results are presented from experiments involving the evolution of radius-3 CA in the Density Classification Task, and radius-2 CA in the Synchronization Task.

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

PubMed Central

Bischofs, Ilka; Price, Gavin; Keasling, Jay; Arkin, Adam P.

2008-01-01

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy. PMID:18324309

Multi-scale volumetric cell and tissue imaging based on optical projection tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ban, Sungbea; Cho, Nam Hyun; Ryu, Yongjae; Jung, Sunwoo; Vavilin, Andrey; Min, Eunjung; Jung, Woonggyu

2016-04-01

Optical projection tomography is a new optical imaging method for visualizing small biological specimens in three dimension. The most important advantage of OPT is to fill the gap between MRI and confocal microscope for the specimen having the range of 1-10 mm. Thus, it has been mainly used for whole-mount small animals and developmental study since this imaging modality was developed. The ability of OPT delivering anatomical and functional information of relatively large tissue in 3D has made it a promising platform in biomedical research. Recently, the potential of OPT spans its coverage to cellular scale. Even though there are increasing demand to obtain better understanding of cellular dynamics, only few studies to visualize cellular structure, shape, size and functional morphology over tissue has been investigated in existing OPT system due to its limited field of view. In this study, we develop a novel optical imaging system for 3D cellular imaging with OPT integrated with dynamic focusing technique. Our tomographic setup has great potential to be used for identifying cell characteristic in tissue because it can provide selective contrast on dynamic focal plane allowing for fluorescence as well as absorption. While the dominant contrast of optical imaging technique is to use the fluorescence for detecting certain target only, the newly developed OPT system will offer considerable advantages over currently available method when imaging cellar molecular dynamics by permitting contrast variation. By achieving multi-contrast, it is expected for this new imaging system to play an important role in delivering better cytological information to pathologist.

Adsorption of charged protein residues on an inorganic nanosheet: Computer simulation of LDH interaction with ion channel

NASA Astrophysics Data System (ADS)

Tsukanov, Alexey A.; Psakhie, Sergey G.

2016-08-01

Quasi-two-dimensional and hybrid nanomaterials based on layered double hydroxides (LDH), cationic clays, layered oxyhydroxides and hydroxides of metals possess large specific surface area and strong electrostatic properties with permanent or pH-dependent electric charge. Such nanomaterials may impact cellular electrostatics, changing the ion balance, pH and membrane potential. Selective ion adsorption/exchange may alter the transmembrane electrochemical gradient, disrupting potential-dependent cellular processes. Cellular proteins as a rule have charged residues which can be effectively adsorbed on the surface of layered hydroxide based nanomaterials. The aim of this study is to attempt to shed some light on the possibility and mechanisms of protein "adhesion" an LDH nanosheet and to propose a new direction in anticancer medicine, based on physical impact and strong electrostatics. An unbiased molecular dynamics simulation was performed and the combined process free energy estimation (COPFEE) approach was used.

Comparative Study of Poly (ε-Caprolactone) and Poly(Lactic-co-Glycolic Acid) -Based Nanofiber Scaffolds for pH-Sensing.

PubMed

Di, Wenjun; Czarny, Ryan S; Fletcher, Nathan A; Krebs, Melissa D; Clark, Heather A

2016-10-01

This study aims to develop biodegradable and biocompatible polymer-based nanofibers that continuously monitor pH within microenvironments of cultured cells in real-time. In the future, these fibers will provide a scaffold for tissue growth while simultaneously monitoring the extracellular environment. Sensors to monitor pH were created by directly electrospinning the sensor components within a polymeric matrix. Specifically, the entire fiber structure is composed of the optical equivalent of an electrode, a pH-sensitive fluorophore, an ionic additive, a plasticizer, and a polymer to impart mechanical stability. The resulting poly(ε-caprolactone) (PCL) and poly(lactic-co-glycolic acid) (PLGA) based sensors were characterized by morphology, dynamic range, reversibility and stability. Since PCL-based nanofibers delivered the most desirable analytical response, this matrix was used for cellular studies. Electrospun nanofiber scaffolds (NFSs) were created directly out of optode material. The resulting NFS sensors respond to pH changes with a dynamic range centered at 7.8 ± 0.1 and 9.6 ± 0.2, for PCL and PLGA respectively. NFSs exhibited multiple cycles of reversibility with a lifetime of at least 15 days with preservation of response characteristics. By comparing the two NFSs, we found PCL-NFSs are more suitable for pH sensing due to their dynamic range and superior reversibility. The proposed sensing platform successfully exhibits a response to pH and compatibility with cultured cells. NSFs will be a useful tool for creating 3D cellular scaffolds that can monitor the cellular environment with applications in fields such as drug discovery and tissue engineering.

Living-Cell Microarrays

PubMed Central

Yarmush, Martin L.; King, Kevin R.

2011-01-01

Living cells are remarkably complex. To unravel this complexity, living-cell assays have been developed that allow delivery of experimental stimuli and measurement of the resulting cellular responses. High-throughput adaptations of these assays, known as living-cell microarrays, which are based on microtiter plates, high-density spotting, microfabrication, and microfluidics technologies, are being developed for two general applications: (a) to screen large-scale chemical and genomic libraries and (b) to systematically investigate the local cellular microenvironment. These emerging experimental platforms offer exciting opportunities to rapidly identify genetic determinants of disease, to discover modulators of cellular function, and to probe the complex and dynamic relationships between cells and their local environment. PMID:19413510

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

The effects of Cosmos caudatus (ulam raja) on dynamic and cellular bone histomorphometry in ovariectomized rats

PubMed Central

2013-01-01

Background Cosmos caudatus is a local plant which has antioxidant properties and contains high calcium. It is also reported to be able to strengthen the bone. This report is an extension to previously published article in Evidence Based Complementary and Alternative Medicine (doi:10.1155/2012/817814). In this study, we determined the effectiveness of C. caudatus as an alternative treatment for osteoporosis due to post-menopause by looking at the dynamic and cellular paramaters of bone histomorphometry. Methods Forty female Wistar rats were divided into four groups i.e. sham operated, ovariectomized, ovariectomized treated with calcium 1% ad libitum and ovariectomized force-fed with 500 mg/kg C. caudatus extract. Treatment was given six days a week for eight weeks. Results Dynamic and cellular histomorphometry parameters were measured. C. caudatus increased double-labeled surface (dLS/BS), mineral appositional rate (MAR), osteoid volume (OV/BV) and osteoblast surface (Ob.S/BS). C. caudatus also gave better results compared to calcium 1% in the osteoid volume (OV/BV) parameter. Conclusions C. caudatus at the 500 mg/kg dose may be an alternative treatment in restoring bone damage that may occur in post-menopausal women. PMID:23800238

The effects of Cosmos caudatus (ulam raja) on dynamic and cellular bone histomorphometry in ovariectomized rats.

PubMed

Mohamed, Norazlina; Sahhugi, Zulaikha; Ramli, Elvy Suhana Mohd; Muhammad, Norliza

2013-06-24

Cosmos caudatus is a local plant which has antioxidant properties and contains high calcium. It is also reported to be able to strengthen the bone. This report is an extension to previously published article in Evidence Based Complementary and Alternative Medicine (doi:10.1155/2012/817814). In this study, we determined the effectiveness of C. caudatus as an alternative treatment for osteoporosis due to post-menopause by looking at the dynamic and cellular paramaters of bone histomorphometry. Forty female Wistar rats were divided into four groups i.e. sham operated, ovariectomized, ovariectomized treated with calcium 1% ad libitum and ovariectomized force-fed with 500 mg/kg C. caudatus extract. Treatment was given six days a week for eight weeks. Dynamic and cellular histomorphometry parameters were measured. C. caudatus increased double-labeled surface (dLS/BS), mineral appositional rate (MAR), osteoid volume (OV/BV) and osteoblast surface (Ob.S/BS). C. caudatus also gave better results compared to calcium 1% in the osteoid volume (OV/BV) parameter. C. caudatus at the 500 mg/kg dose may be an alternative treatment in restoring bone damage that may occur in post-menopausal women.

Photocrosslinking approaches to interactome mapping

PubMed Central

Pham, Nam D.; Parker, Randy B.; Kohler, Jennifer J.

2012-01-01

Photocrosslinking approaches can be used to map interactome networks within the context of living cells. Photocrosslinking methods rely on use of metabolic engineering or genetic code expansion to incorporate photocrosslinking analogs of amino acids or sugars into cellular biomolecules. Immunological and mass spectrometry techniques are used to analyze crosslinked complexes, thereby defining specific interactomes. Because photocrosslinking can be conducted in native, cellular settings, it can be used to define context-dependent interactions. Photocrosslinking methods are also ideally suited for determining interactome dynamics, mapping interaction interfaces, and identifying transient interactions in which intrinsically disordered proteins and glycoproteins engage. Here we discuss the application of cell-based photocrosslinking to the study of specific problems in immune cell signaling, transcription, membrane protein dynamics, nucleocytoplasmic transport, and chaperone-assisted protein folding. PMID:23149092

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications

PubMed Central

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O.

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n2 memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach. PMID:26578867

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

PubMed Central

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-01-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer. PMID:26876008

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

PubMed

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

NASA Astrophysics Data System (ADS)

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-02-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer.

Reversible elementary cellular automaton with rule number 150 and periodic boundary conditions over 𝔽p

NASA Astrophysics Data System (ADS)

Martín Del Rey, A.; Rodríguez Sánchez, G.

2015-03-01

The study of the reversibility of elementary cellular automata with rule number 150 over the finite state set 𝔽p and endowed with periodic boundary conditions is done. The dynamic of such discrete dynamical systems is characterized by means of characteristic circulant matrices, and their analysis allows us to state that the reversibility depends on the number of cells of the cellular space and to explicitly compute the corresponding inverse cellular automata.

Model-based cell number quantification using online single-oxygen sensor data for tissue engineering perfusion bioreactors.

PubMed

Lambrechts, T; Papantoniou, I; Sonnaert, M; Schrooten, J; Aerts, J-M

2014-10-01

Online and non-invasive quantification of critical tissue engineering (TE) construct quality attributes in TE bioreactors is indispensable for the cost-effective up-scaling and automation of cellular construct manufacturing. However, appropriate monitoring techniques for cellular constructs in bioreactors are still lacking. This study presents a generic and robust approach to determine cell number and metabolic activity of cell-based TE constructs in perfusion bioreactors based on single oxygen sensor data in dynamic perfusion conditions. A data-based mechanistic modeling technique was used that is able to correlate the number of cells within the scaffold (R(2)  = 0.80) and the metabolic activity of the cells (R(2)  = 0.82) to the dynamics of the oxygen response to step changes in the perfusion rate. This generic non-destructive measurement technique is effective for a large range of cells, from as low as 1.0 × 10(5) cells to potentially multiple millions of cells, and can open-up new possibilities for effective bioprocess monitoring. © 2014 Wiley Periodicals, Inc.

Systematic Computation of Nonlinear Cellular and Molecular Dynamics with Low-Power CytoMimetic Circuits: A Simulation Study

PubMed Central

Papadimitriou, Konstantinos I.; Stan, Guy-Bart V.; Drakakis, Emmanuel M.

2013-01-01

This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented. PMID:23393550

3D Time-lapse Imaging and Quantification of Mitochondrial Dynamics

NASA Astrophysics Data System (ADS)

Sison, Miguel; Chakrabortty, Sabyasachi; Extermann, Jérôme; Nahas, Amir; James Marchand, Paul; Lopez, Antonio; Weil, Tanja; Lasser, Theo

2017-02-01

We present a 3D time-lapse imaging method for monitoring mitochondrial dynamics in living HeLa cells based on photothermal optical coherence microscopy and using novel surface functionalization of gold nanoparticles. The biocompatible protein-based biopolymer coating contains multiple functional groups which impart better cellular uptake and mitochondria targeting efficiency. The high stability of the gold nanoparticles allows continuous imaging over an extended time up to 3000 seconds without significant cell damage. By combining temporal autocorrelation analysis with a classical diffusion model, we quantify mitochondrial dynamics and cast these results into 3D maps showing the heterogeneity of diffusion parameters across the whole cell volume.

Integrated cellular network of transcription regulations and protein-protein interactions

PubMed Central

2010-01-01

Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology. PMID:20211003

Integrated cellular network of transcription regulations and protein-protein interactions.

PubMed

Wang, Yu-Chao; Chen, Bor-Sen

2010-03-08

With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

Evolution of cellular automata with memory: The Density Classification Task.

PubMed

Stone, Christopher; Bull, Larry

2009-08-01

The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.

A Multi-Paradigm Modeling Framework to Simulate Dynamic Reciprocity in a Bioreactor

PubMed Central

Kaul, Himanshu; Cui, Zhanfeng; Ventikos, Yiannis

2013-01-01

Despite numerous technology advances, bioreactors are still mostly utilized as functional black-boxes where trial and error eventually leads to the desirable cellular outcome. Investigators have applied various computational approaches to understand the impact the internal dynamics of such devices has on overall cell growth, but such models cannot provide a comprehensive perspective regarding the system dynamics, due to limitations inherent to the underlying approaches. In this study, a novel multi-paradigm modeling platform capable of simulating the dynamic bidirectional relationship between cells and their microenvironment is presented. Designing the modeling platform entailed combining and coupling fully an agent-based modeling platform with a transport phenomena computational modeling framework. To demonstrate capability, the platform was used to study the impact of bioreactor parameters on the overall cell population behavior and vice versa. In order to achieve this, virtual bioreactors were constructed and seeded. The virtual cells, guided by a set of rules involving the simulated mass transport inside the bioreactor, as well as cell-related probabilistic parameters, were capable of displaying an array of behaviors such as proliferation, migration, chemotaxis and apoptosis. In this way the platform was shown to capture not only the impact of bioreactor transport processes on cellular behavior but also the influence that cellular activity wields on that very same local mass transport, thereby influencing overall cell growth. The platform was validated by simulating cellular chemotaxis in a virtual direct visualization chamber and comparing the simulation with its experimental analogue. The results presented in this paper are in agreement with published models of similar flavor. The modeling platform can be used as a concept selection tool to optimize bioreactor design specifications. PMID:23555740

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

PubMed

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Application of Petri Nets in Bone Remodeling

PubMed Central

Li, Lingxi; Yokota, Hiroki

2009-01-01

Understanding a mechanism of bone remodeling is a challenging task for both life scientists and model builders, since this highly interactive and nonlinear process can seldom be grasped by simple intuition. A set of ordinary differential equations (ODEs) have been built for simulating bone formation as well as bone resorption. Although solving ODEs numerically can provide useful predictions for dynamical behaviors in a continuous time frame, an actual bone remodeling process in living tissues is driven by discrete events of molecular and cellular interactions. Thus, an event-driven tool such as Petri nets (PNs), which may dynamically and graphically mimic individual molecular collisions or cellular interactions, seems to augment the existing ODE-based systems analysis. Here, we applied PNs to expand the ODE-based approach and examined discrete, dynamical behaviors of key regulatory molecules and bone cells. PNs have been used in many engineering areas, but their application to biological systems needs to be explored. Our PN model was based on 8 ODEs that described an osteoprotegerin linked molecular pathway consisting of 4 types of bone cells. The models allowed us to conduct both qualitative and quantitative evaluations and evaluate homeostatic equilibrium states. The results support that application of PN models assists understanding of an event-driven bone remodeling mechanism using PN-specific procedures such as places, transitions, and firings. PMID:19838338

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Compartmental genomics in living cells revealed by single-cell nanobiopsy.

PubMed

Actis, Paolo; Maalouf, Michelle M; Kim, Hyunsung John; Lohith, Akshar; Vilozny, Boaz; Seger, R Adam; Pourmand, Nader

2014-01-28

The ability to study the molecular biology of living single cells in heterogeneous cell populations is essential for next generation analysis of cellular circuitry and function. Here, we developed a single-cell nanobiopsy platform based on scanning ion conductance microscopy (SICM) for continuous sampling of intracellular content from individual cells. The nanobiopsy platform uses electrowetting within a nanopipette to extract cellular material from living cells with minimal disruption of the cellular milieu. We demonstrate the subcellular resolution of the nanobiopsy platform by isolating small subpopulations of mitochondria from single living cells, and quantify mutant mitochondrial genomes in those single cells with high throughput sequencing technology. These findings may provide the foundation for dynamic subcellular genomic analysis.

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Dynamic Microenvironment Induces Phenotypic Plasticity of Esophageal Cancer Cells Under Flow

NASA Astrophysics Data System (ADS)

Calibasi Kocal, Gizem; Güven, Sinan; Foygel, Kira; Goldman, Aaron; Chen, Pu; Sengupta, Shiladitya; Paulmurugan, Ramasamy; Baskin, Yasemin; Demirci, Utkan

2016-12-01

Cancer microenvironment is a remarkably heterogeneous composition of cellular and non-cellular components, regulated by both external and intrinsic physical and chemical stimuli. Physical alterations driven by increased proliferation of neoplastic cells and angiogenesis in the cancer microenvironment result in the exposure of the cancer cells to elevated levels of flow-based shear stress. We developed a dynamic microfluidic cell culture platform utilizing eshopagael cancer cells as model cells to investigate the phenotypic changes of cancer cells upon exposure to fluid shear stress. We report the epithelial to hybrid epithelial/mesenchymal transition as a result of decreasing E-Cadherin and increasing N-Cadherin and vimentin expressions, higher clonogenicity and ALDH positive expression of cancer cells cultured in a dynamic microfluidic chip under laminar flow compared to the static culture condition. We also sought regulation of chemotherapeutics in cancer microenvironment towards phenotypic control of cancer cells. Such in vitro microfluidic system could potentially be used to monitor how the interstitial fluid dynamics affect cancer microenvironment and plasticity on a simple, highly controllable and inexpensive bioengineered platform.

Physical Model of the Dynamic Instability in an Expanding Cell Culture

PubMed Central

Mark, Shirley; Shlomovitz, Roie; Gov, Nir S.; Poujade, Mathieu; Grasland-Mongrain, Erwan; Silberzan, Pascal

2010-01-01

Abstract Collective cell migration is of great significance in many biological processes. The goal of this work is to give a physical model for the dynamics of cell migration during the wound healing response. Experiments demonstrate that an initially uniform cell-culture monolayer expands in a nonuniform manner, developing fingerlike shapes. These fingerlike shapes of the cell culture front are composed of columns of cells that move collectively. We propose a physical model to explain this phenomenon, based on the notion of dynamic instability. In this model, we treat the first layers of cells at the front of the moving cell culture as a continuous one-dimensional membrane (contour), with the usual elasticity of a membrane: curvature and surface-tension. This membrane is active, due to the forces of cellular motility of the cells, and we propose that this motility is related to the local curvature of the culture interface; larger convex curvature correlates with a stronger cellular motility force. This shape-force relation gives rise to a dynamic instability, which we then compare to the patterns observed in the wound healing experiments. PMID:20141748

The Virtual Cell Animation Collection: Tools for Teaching Molecular and Cellular Biology

PubMed Central

Reindl, Katie M.; White, Alan R.; Johnson, Christina; Vender, Bradley; Slator, Brian M.; McClean, Phillip

2015-01-01

A cell is a minifactory in which structures and molecules are assembled, rearranged, disassembled, packaged, sorted, and transported. Because cellular structures and molecules are invisible to the human eye, students often have difficulty conceptualizing the dynamic nature of cells that function at multiple scales across time and space. To represent these dynamic cellular processes, the Virtual Cell Productions team at North Dakota State University develops freely available multimedia materials to support molecular and cellular biology learning inside and outside the high school and university classroom. PMID:25856580

Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

Cell death and renewal during prey capture and digestion in the carnivorous sponge Asbestopluma hypogea (Porifera: Poecilosclerida).

PubMed

Martinand-Mari, Camille; Vacelet, Jean; Nickel, Michael; Wörheide, Gert; Mangeat, Paul; Baghdiguian, Stephen

2012-11-15

The sponge Asbestopluma hypogea is unusual among sponges due to its peculiar carnivorous feeding habit. During various stages of its nutrition cycle, the sponge is subjected to spectacular morphological modifications. Starved animals are characterized by many elongated filaments, which are crucial for the capture of prey. After capture, and during the digestion process, these filaments actively regress before being regenerated during a subsequent period of starvation. Here, we demonstrate that these morphological events rely on a highly dynamic cellular turnover, implying a coordinated sequence of programmed cell death (apoptosis and autophagy), cell proliferation and cell migration. A candidate niche for cell renewal by stem cell proliferation and differentiation was identified at the base of the sponge peduncle, characterized by higher levels of BrdU/EdU incorporation. Therefore, BrdU/EdU-positive cells of the peduncle base are candidate motile cells responsible for the regeneration of the prey-capturing main sponge body, i.e. the dynamic filaments. Altogether, our results demonstrate that dynamics of cell renewal in sponge appear to be regulated by cellular mechanisms as multiple and complex as those already identified in bilaterian metazoans.

Dynamic photopatterning of cells in situ by Q-switched neodymium-doped yttrium ortho-vanadate laser.

PubMed

Deka, Gitanjal; Okano, Kazunori; Kao, Fu-Jen

2014-01-01

Cellular micropattering has been increasingly adopted in quantitative biological experiments. A Q-switched pulsed neodymium-doped yttrium ortho-vanadate (Nd∶YVO4) laser directed in-situ microfabrication technique for cell patterning is presented. A platform is designed uniquely to achieve laser ablation. The platform is comprised of thin gold coating over a glass surface that functions as a thermal transducer and is over-layered by a cell repellant polymer layer. Micropatterns are engraved on the platform, subsequently exposing specific cell adhesive micro-domains by ablating the gold-polymer coating photothermally. Experimental results indicate that the proposed approach is applicable under culture conditions, viable toward cells, and has a higher engraving speed. Possible uses in arraying isolated single cells on the platform are also shown. Additionally, based on those micro-patterns, dynamic cellular morphological changes and migrational speed in response to geometrical barriers are studied to demonstrate the potential applications of the proposed approach. Our results further demonstrate that cells in narrower geometry had elongated shapes and higher migrational speed than those in wider geometry. Importantly, the proposed approach will provide a valuable reference for efforts to study single cell dynamics and cellular migration related processes for areas such as cell division, wound healing, and cancer invasion.

Simulation of emotional contagion using modified SIR model: A cellular automaton approach

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

2014-07-01

Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

Modelling chronotaxicity of cellular energy metabolism to facilitate the identification of altered metabolic states

NASA Astrophysics Data System (ADS)

Lancaster, Gemma; Suprunenko, Yevhen F.; Jenkins, Kirsten; Stefanovska, Aneta

2016-08-01

Altered cellular energy metabolism is a hallmark of many diseases, one notable example being cancer. Here, we focus on the identification of the transition from healthy to abnormal metabolic states. To do this, we study the dynamics of energy production in a cell. Due to the thermodynamic openness of a living cell, the inability to instantaneously match fluctuating supply and demand in energy metabolism results in nonautonomous time-varying oscillatory dynamics. However, such oscillatory dynamics is often neglected and treated as stochastic. Based on experimental evidence of metabolic oscillations, we show that changes in metabolic state can be described robustly by alterations in the chronotaxicity of the corresponding metabolic oscillations, i.e. the ability of an oscillator to resist external perturbations. We also present a method for the identification of chronotaxicity, applicable to general oscillatory signals and, importantly, apply this to real experimental data. Evidence of chronotaxicity was found in glycolytic oscillations in real yeast cells, verifying that chronotaxicity could be used to study transitions between metabolic states.

Dendritic spine dynamics in synaptogenesis after repeated LTP inductions: Dependence on pre-existing spine density

PubMed Central

Oe, Yuki; Tominaga-Yoshino, Keiko; Hasegawa, Sho; Ogura, Akihiko

2013-01-01

Not only from our daily experience but from learning experiments in animals, we know that the establishment of long-lasting memory requires repeated practice. However, cellular backgrounds underlying this repetition-dependent consolidation of memory remain largely unclear. We reported previously using organotypic slice cultures of rodent hippocampus that the repeated inductions of LTP (long-term potentiation) lead to a slowly developing long-lasting synaptic enhancement accompanied by synaptogenesis distinct from LTP itself, and proposed this phenomenon as a model system suitable for the analysis of the repetition-dependent consolidation of memory. Here we examined the dynamics of individual dendritic spines after repeated LTP-inductions and found the existence of two phases in the spines' stochastic behavior that eventually lead to the increase in spine density. This spine dynamics occurred preferentially in the dendritic segments having low pre-existing spine density. Our results may provide clues for understanding the cellular bases underlying the repetition-dependent consolidation of memory. PMID:23739837

Ultrasensitive dual phosphorylation dephosphorylation cycle kinetics exhibits canonical competition behavior

NASA Astrophysics Data System (ADS)

Huang, Qingdao; Qian, Hong

2009-09-01

We establish a mathematical model for a cellular biochemical signaling module in terms of a planar differential equation system. The signaling process is carried out by two phosphorylation-dephosphorylation reaction steps that share common kinase and phosphatase with saturated enzyme kinetics. The pair of equations is particularly simple in the present mathematical formulation, but they are singular. A complete mathematical analysis is developed based on an elementary perturbation theory. The dynamics exhibits the canonical competition behavior in addition to bistability. Although widely understood in ecological context, we are not aware of a full range of biochemical competition in a simple signaling network. The competition dynamics has broad implications to cellular processes such as cell differentiation and cancer immunoediting. The concepts of homogeneous and heterogeneous multisite phosphorylation are introduced and their corresponding dynamics are compared: there is no bistability in a heterogeneous dual phosphorylation system. A stochastic interpretation is also provided that further gives intuitive understanding of the bistable behavior inside the cells.

Correlated receptor transport processes buffer single-cell heterogeneity

PubMed Central

Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland

2017-01-01

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754

Robust and irreversible development in cell society as a general consequence of intra-inter dynamics

NASA Astrophysics Data System (ADS)

Kaneko, Kunihiko; Furusawa, Chikara

2000-05-01

A dynamical systems scenario for developmental cell biology is proposed, based on numerical studies of a system with interacting units with internal dynamics and reproduction. Diversification, formation of discrete and recursive types, and rules for differentiation are found as a natural consequence of such a system. “Stem cells” that either proliferate or differentiate to different types stochastically are found to appear when intra-cellular dynamics are chaotic. Robustness of the developmental process against microscopic and macroscopic perturbations is shown to be a natural consequence of such intra-inter dynamics, while irreversibility in developmental process is discussed in terms of the gain of stability, loss of diversity and chaotic instability.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

PubMed

Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

Quantifying the driving factors for language shift in a bilingual region.

PubMed

Prochazka, Katharina; Vogl, Gero

2017-04-25

Many of the world's around 6,000 languages are in danger of disappearing as people give up use of a minority language in favor of the majority language in a process called language shift. Language shift can be monitored on a large scale through the use of mathematical models by way of differential equations, for example, reaction-diffusion equations. Here, we use a different approach: we propose a model for language dynamics based on the principles of cellular automata/agent-based modeling and combine it with very detailed empirical data. Our model makes it possible to follow language dynamics over space and time, whereas existing models based on differential equations average over space and consequently provide no information on local changes in language use. Additionally, cellular automata models can be used even in cases where models based on differential equations are not applicable, for example, in situations where one language has become dispersed and retreated to language islands. Using data from a bilingual region in Austria, we show that the most important factor in determining the spread and retreat of a language is the interaction with speakers of the same language. External factors like bilingual schools or parish language have only a minor influence.

Probabilistic Cellular Automata

PubMed Central

Agapie, Alexandru; Giuclea, Marius

2014-01-01

Abstract Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case—connecting the probability of a configuration in the stationary distribution to its number of zero-one borders—the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557

Probabilistic cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

Coordination of Cellular Dynamics Contributes to Tooth Epithelium Deformations

PubMed Central

Morita, Ritsuko; Kihira, Miho; Nakatsu, Yousuke; Nomoto, Yohei; Ogawa, Miho; Ohashi, Kazumasa; Mizuno, Kensaku; Tachikawa, Tetsuhiko; Ishimoto, Yukitaka; Morishita, Yoshihiro; Tsuji, Takashi

2016-01-01

The morphologies of ectodermal organs are shaped by appropriate combinations of several deformation modes, such as invagination and anisotropic tissue elongation. However, how multicellular dynamics are coordinated during deformation processes remains to be elucidated. Here, we developed a four-dimensional (4D) analysis system for tracking cell movement and division at a single-cell resolution in developing tooth epithelium. The expression patterns of a Fucci probe clarified the region- and stage-specific cell cycle patterns within the tooth germ, which were in good agreement with the pattern of the volume growth rate estimated from tissue-level deformation analysis. Cellular motility was higher in the regions with higher growth rates, while the mitotic orientation was significantly biased along the direction of tissue elongation in the epithelium. Further, these spatio-temporal patterns of cellular dynamics and tissue-level deformation were highly correlated with that of the activity of cofilin, which is an actin depolymerization factor, suggesting that the coordination of cellular dynamics via actin remodeling plays an important role in tooth epithelial morphogenesis. Our system enhances the understanding of how cellular behaviors are coordinated during ectodermal organogenesis, which cannot be observed from histological analyses. PMID:27588418

A cellular automaton for the signed particle formulation of quantum mechanics

NASA Astrophysics Data System (ADS)

Sellier, J. M.; Kapanova, K. G.; Dimov, I.

2017-02-01

Recently, a new formulation of quantum mechanics, based on the concept of signed particles, has been suggested. In this paper, we introduce a cellular automaton which mimics the dynamics of quantum objects in the phase-space in a time-dependent fashion. This is twofold: it provides a simplified and accessible language to non-physicists who wants to simulate quantum mechanical systems, at the same time it enables a different way to explore the laws of Physics. Moreover, it opens the way towards hybrid simulations of quantum systems by combining full quantum models with cellular automata when the former fail. In order to show the validity of the suggested cellular automaton and its combination with the signed particle formalism, several numerical experiments are performed, showing very promising results. Being this article a preliminary study on quantum simulations in phase-space by means of cellular automata, some conclusions are drawn about the encouraging results obtained so far and the possible future developments.

Compartmental Genomics in Living Cells Revealed by Single-Cell Nanobiopsy

PubMed Central

Actis, Paolo; Maalouf, Michelle; Kim, Hyunsung John; Lohith, Akshar; Vilozny, Boaz; Seger, R. Adam; Pourmand, Nader

2014-01-01

The ability to study the molecular biology of living single cells in heterogeneous cell populations is essential for next generation analysis of cellular circuitry and function. Here, we developed a single-cell nanobiopsy platform based on scanning ion conductance microscopy (SICM) for continuous sampling of intracellular content from individual cells. The nanobiopsy platform uses electrowetting within a nanopipette to extract cellular material from living cells with minimal disruption of the cellular milieu. We demonstrate the subcellular resolution of the nanobiopsy platform by isolating small subpopulations of mitochondria from single living cells, and quantify mutant mitochondrial genomes in those single cells with high throughput sequencing technology. These findings may provide the foundation for dynamic subcellular genomic analysis. PMID:24279711

Cellular dynamics of bovine aortic smooth muscle cells measured using MEMS force sensors

NASA Astrophysics Data System (ADS)

Tsukagoshi, Takuya; Nguyen, Thanh-Vinh; Hirayama Shoji, Kayoko; Takahashi, Hidetoshi; Matsumoto, Kiyoshi; Shimoyama, Isao

2018-04-01

Adhesive cells perceive the mechanical properties of the substrates to which they adhere, adjusting their cellular mechanical forces according to their biological characteristics. This mechanical interaction subsequently affects the growth, locomotion, and differentiation of the cell. However, little is known about the detailed mechanism that underlies this interaction between adherent cells and substrates because dynamically measuring mechanical phenomena is difficult. Here, we utilize microelectromechamical systems force sensors that can measure cellular traction forces with high temporal resolution (~2.5 µs) over long periods (~3 h). We found that the cellular dynamics reflected physical phenomena with time scales from milliseconds to hours, which contradicts the idea that cellular motion is slow. A single focal adhesion (FA) generates an average force of 7 nN, which disappears in ms via the action of trypsin-ethylenediaminetetraacetic acid. The force-changing rate obtained from our measurements suggests that the time required for an FA to decompose was nearly proportional to the force acting on the FA.

A novel image encryption algorithm using chaos and reversible cellular automata

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Luan, Dapeng

2013-11-01

In this paper, a novel image encryption scheme is proposed based on reversible cellular automata (RCA) combining chaos. In this algorithm, an intertwining logistic map with complex behavior and periodic boundary reversible cellular automata are used. We split each pixel of image into units of 4 bits, then adopt pseudorandom key stream generated by the intertwining logistic map to permute these units in confusion stage. And in diffusion stage, two-dimensional reversible cellular automata which are discrete dynamical systems are applied to iterate many rounds to achieve diffusion on bit-level, in which we only consider the higher 4 bits in a pixel because the higher 4 bits carry almost the information of an image. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack. This algorithm belongs to the class of symmetric systems.

Red blood cell dynamics: from cell deformation to ATP release.

PubMed

Wan, Jiandi; Forsyth, Alison M; Stone, Howard A

2011-10-01

The mechanisms of red blood cell (RBC) deformation under both static and dynamic, i.e., flow, conditions have been studied extensively since the mid 1960s. Deformation-induced biochemical reactions and possible signaling in RBCs, however, were proposed only fifteen years ago. Therefore, the fundamental relationship between RBC deformation and cellular signaling dynamics i.e., mechanotransduction, remains incompletely understood. Quantitative understanding of the mechanotransductive pathways in RBCs requires integrative studies of physical models of RBC deformation and cellular biochemical reactions. In this article we review the physical models of RBC deformation, spanning from continuum membrane mechanics to cellular skeleton dynamics under both static and flow conditions, and elaborate the mechanistic links involved in deformation-induced ATP release. This journal is © The Royal Society of Chemistry 2011

Physical Modeling of Microtubules Network

NASA Astrophysics Data System (ADS)

Allain, Pierre; Kervrann, Charles

2014-10-01

Microtubules (MT) are highly dynamic tubulin polymers that are involved in many cellular processes such as mitosis, intracellular cell organization and vesicular transport. Nevertheless, the modeling of cytoskeleton and MT dynamics based on physical properties is difficult to achieve. Using the Euler-Bernoulli beam theory, we propose to model the rigidity of microtubules on a physical basis using forces, mass and acceleration. In addition, we link microtubules growth and shrinkage to the presence of molecules (e.g. GTP-tubulin) in the cytosol. The overall model enables linking cytosol to microtubules dynamics in a constant state space thus allowing usage of data assimilation techniques.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Computational Systems Toxicology: recapitulating the logistical dynamics of cellular response networks in virtual tissue models (Eurotox_2017)

EPA Science Inventory

Translating in vitro data and biological information into a predictive model for human toxicity poses a significant challenge. This is especially true for complex adaptive systems such as the embryo where cellular dynamics are precisely orchestrated in space and time. Computer ce...

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory.

PubMed

Hasselmo, Michael E; Giocomo, Lisa M; Brandon, Mark P; Yoshida, Motoharu

2010-12-31

Understanding the mechanisms of episodic memory requires linking behavioral data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. Copyright © 2010 Elsevier B.V. All rights reserved.

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory

PubMed Central

Hasselmo, Michael E.; Giocomo, Lisa M.; Yoshida, Motoharu

2010-01-01

Understanding the mechanisms of episodic memory requires linking behavioural data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within these brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. PMID:20018213

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

An introduction to NMR-based approaches for measuring protein dynamics

PubMed Central

Kleckner, Ian R; Foster, Mark P

2010-01-01

Proteins are inherently flexible at ambient temperature. At equilibrium, they are characterized by a set of conformations that undergo continuous exchange within a hierarchy of spatial and temporal scales ranging from nanometers to micrometers and femtoseconds to hours. Dynamic properties of proteins are essential for describing the structural bases of their biological functions including catalysis, binding, regulation and cellular structure. Nuclear magnetic resonance (NMR) spectroscopy represents a powerful technique for measuring these essential features of proteins. Here we provide an introduction to NMR-based approaches for studying protein dynamics, highlighting eight distinct methods with recent examples, contextualized within a common experimental and analytical framework. The selected methods are (1) Real-time NMR, (2) Exchange spectroscopy, (3) Lineshape analysis, (4) CPMG relaxation dispersion, (5) Rotating frame relaxation dispersion, (6) Nuclear spin relaxation, (7) Residual dipolar coupling, (8) Paramagnetic relaxation enhancement. PMID:21059410

The salt marsh vegetation spread dynamics simulation and prediction based on conditions optimized CA

NASA Astrophysics Data System (ADS)

Guan, Yujuan; Zhang, Liquan

2006-10-01

The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin

PubMed Central

Fuchs, Julian E.; Huber, Roland G.; Waldner, Birgit J.; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design. PMID:26496636

Toward a systems-level view of dynamic phosphorylation networks

PubMed Central

Newman, Robert H.; Zhang, Jin; Zhu, Heng

2014-01-01

To better understand how cells sense and respond to their environment, it is important to understand the organization and regulation of the phosphorylation networks that underlie most cellular signal transduction pathways. These networks, which are composed of protein kinases, protein phosphatases and their respective cellular targets, are highly dynamic. Importantly, to achieve signaling specificity, phosphorylation networks must be regulated at several levels, including at the level of protein expression, substrate recognition, and spatiotemporal modulation of enzymatic activity. Here, we briefly summarize some of the traditional methods used to study the phosphorylation status of cellular proteins before focusing our attention on several recent technological advances, such as protein microarrays, quantitative mass spectrometry, and genetically-targetable fluorescent biosensors, that are offering new insights into the organization and regulation of cellular phosphorylation networks. Together, these approaches promise to lead to a systems-level view of dynamic phosphorylation networks. PMID:25177341

Altered Cell Mechanics from the Inside: Dispersed Single Wall Carbon Nanotubes Integrate with and Restructure Actin

PubMed Central

Holt, Brian D.; Shams, Hengameh; Horst, Travis A.; Basu, Saurav; Rape, Andrew D.; Wang, Yu-Li; Rohde, Gustavo K.; Mofrad, Mohammad R. K.; Islam, Mohammad F.; Dahl, Kris Noel

2012-01-01

With a range of desirable mechanical and optical properties, single wall carbon nanotubes (SWCNTs) are a promising material for nanobiotechnologies. SWCNTs also have potential as biomaterials for modulation of cellular structures. Previously, we showed that highly purified, dispersed SWCNTs grossly alter F-actin inside cells. F-actin plays critical roles in the maintenance of cell structure, force transduction, transport and cytokinesis. Thus, quantification of SWCNT-actin interactions ranging from molecular, sub-cellular and cellular levels with both structure and function is critical for developing SWCNT-based biotechnologies. Further, this interaction can be exploited, using SWCNTs as a unique actin-altering material. Here, we utilized molecular dynamics simulations to explore the interactions of SWCNTs with actin filaments. Fluorescence lifetime imaging microscopy confirmed that SWCNTs were located within ~5 nm of F-actin in cells but did not interact with G-actin. SWCNTs did not alter myosin II sub-cellular localization, and SWCNT treatment in cells led to significantly shorter actin filaments. Functionally, cells with internalized SWCNTs had greatly reduced cell traction force. Combined, these results demonstrate direct, specific SWCNT alteration of F-actin structures which can be exploited for SWCNT-based biotechnologies and utilized as a new method to probe fundamental actin-related cellular processes and biophysics. PMID:24955540

Nuclear Cytoplasmic Trafficking of Proteins is a Major Response of Human Fibroblasts to Oxidative Stress

PubMed Central

Baqader, Noor O.; Radulovic, Marko; Crawford, Mark; Stoeber, Kai; Godovac-Zimmermann, Jasminka

2014-01-01

We have used a subcellular spatial razor approach based on LC–MS/MS-based proteomics with SILAC isotope labeling to determine changes in protein abundances in the nuclear and cytoplasmic compartments of human IMR90 fibroblasts subjected to mild oxidative stress. We show that response to mild tert-butyl hydrogen peroxide treatment includes redistribution between the nucleus and cytoplasm of numerous proteins not previously associated with oxidative stress. The 121 proteins with the most significant changes encompass proteins with known functions in a wide variety of subcellular locations and of cellular functional processes (transcription, signal transduction, autophagy, iron metabolism, TCA cycle, ATP synthesis) and are consistent with functional networks that are spatially dispersed across the cell. Both nuclear respiratory factor 2 and the proline regulatory axis appear to contribute to the cellular metabolic response. Proteins involved in iron metabolism or with iron/heme as a cofactor as well as mitochondrial proteins are prominent in the response. Evidence suggesting that nuclear import/export and vesicle-mediated protein transport contribute to the cellular response was obtained. We suggest that measurements of global changes in total cellular protein abundances need to be complemented with measurements of the dynamic subcellular spatial redistribution of proteins to obtain comprehensive pictures of cellular function. PMID:25133973

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Singh, Surya Prakash

2017-11-01

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10-30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine-cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.

A propagating ATPase gradient drives transport of surface-confined cellular cargo

NASA Astrophysics Data System (ADS)

Vecchiarelli, Anthony; Neuman, Keir; Mizuuchi, Kiyoshi

2014-03-01

The process of DNA segregation is of central importance for all organisms. Although eukaryotic mitosis is relatively well established, the most common mechanism employed for bacterial DNA segregation has been unclear. ParA ATPases form dynamic patterns on the bacterial nucleoid, to spatially organize plasmids, chromosomes and other large cellular cargo, but the force generating mechanism has been a source of controversy and debate. A dominant view proposes that ParA-mediated transport and cargo positioning occurs via a filament-based mechanism that resembles eukaryotic mitosis. Here we present direct evidence against such models. Our cell-free reconstitution supports a non-filament-based mode of transport that may be as widely found in nature as actin filaments and microtubules.

Current status and perspectives in atomic force microscopy-based identification of cellular transformation

PubMed Central

Dong, Chenbo; Hu, Xiao; Dinu, Cerasela Zoica

2016-01-01

Understanding the complex interplay between cells and their biomechanics and how the interplay is influenced by the extracellular microenvironment, as well as how the transforming potential of a tissue from a benign to a cancerous one is related to the dynamics of both the cell and its surroundings, holds promise for the development of targeted translational therapies. This review provides a comprehensive overview of atomic force microscopy-based technology and its applications for identification of cellular progression to a cancerous phenotype. The review also offers insights into the advancements that are required for the next user-controlled tool to allow for the identification of early cell transformation and thus potentially lead to improved therapeutic outcomes. PMID:27274238

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804

Miniaturized integration of a fluorescence microscope

PubMed Central

Ghosh, Kunal K.; Burns, Laurie D.; Cocker, Eric D.; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J.

2013-01-01

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals towards relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including semiconductor light source and sensor. This device enables high-speed cellular-level imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens. PMID:21909102

Miniaturized integration of a fluorescence microscope.

PubMed

Ghosh, Kunal K; Burns, Laurie D; Cocker, Eric D; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J

2011-09-11

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals for relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including a semiconductor light source and sensor. This device enables high-speed cellular imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens.

Long Time-lapse Nanoscopy with Spontaneously Blinking Membrane Probes

PubMed Central

Takakura, Hideo; Zhang, Yongdeng; Erdmann, Roman S.; Thompson, Alexander D.; Lin, Yu; McNellis, Brian; Rivera-Molina, Felix; Uno, Shin-nosuke; Kamiya, Mako; Urano, Yasuteru; Rothman, James E.; Bewersdorf, Joerg; Schepartz, Alanna; Toomre, Derek

2017-01-01

Long time-lapse, diffraction-unlimited super-resolution imaging of cellular structures and organelles in living cells is highly challenging, as it requires dense labeling, bright, highly photostable dyes, and non-toxic conditions. We developed a set of high-density, environment-sensitive (HIDE) membrane probes based on HMSiR that assemble in situ and enable long time-lapse, live cell nanoscopy of discrete cellular structures and organelles with high spatio-temporal resolution. HIDE-enabled nanoscopy movies are up to 50x longer than movies obtained with labeled proteins, reveal the 2D dynamics of the mitochondria, plasma membrane, and filopodia, and the 2D and 3D dynamics of the endoplasmic reticulum in living cells. These new HIDE probes also facilitate the acquisition of live cell, two-color, super-resolution images, greatly expanding the utility of nanoscopy to visualize processes and structures in living cells. PMID:28671662

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

NASA Astrophysics Data System (ADS)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Extrasynaptic Glutamate Receptor Activation as Cellular Bases for Dynamic Range Compression in Pyramidal Neurons

PubMed Central

Oikonomou, Katerina D.; Short, Shaina M.; Rich, Matthew T.; Antic, Srdjan D.

2012-01-01

Repetitive synaptic stimulation overcomes the ability of astrocytic processes to clear glutamate from the extracellular space, allowing some dendritic segments to become submerged in a pool of glutamate, for a brief period of time. This dynamic arrangement activates extrasynaptic NMDA receptors located on dendritic shafts. We used voltage-sensitive and calcium-sensitive dyes to probe dendritic function in this glutamate-rich location. An excess of glutamate in the extrasynaptic space was achieved either by repetitive synaptic stimulation or by glutamate iontophoresis onto the dendrites of pyramidal neurons. Two successive activations of synaptic inputs produced a typical NMDA spike, whereas five successive synaptic inputs produced characteristic plateau potentials, reminiscent of cortical UP states. While NMDA spikes were coupled with brief calcium transients highly restricted to the glutamate input site, the dendritic plateau potentials were accompanied by calcium influx along the entire dendritic branch. Once initiated, the glutamate-mediated dendritic plateau potentials could not be interrupted by negative voltage pulses. Activation of extrasynaptic NMDA receptors in cellular compartments void of spines is sufficient to initiate and support plateau potentials. The only requirement for sustained depolarizing events is a surplus of free glutamate near a group of extrasynaptic receptors. Highly non-linear dendritic spikes (plateau potentials) are summed in a highly sublinear fashion at the soma, revealing the cellular bases of signal compression in cortical circuits. Extrasynaptic NMDA receptors provide pyramidal neurons with a function analogous to a dynamic range compression in audio engineering. They limit or reduce the volume of “loud sounds” (i.e., strong glutamatergic inputs) and amplify “quiet sounds” (i.e., glutamatergic inputs that barely cross the dendritic threshold for local spike initiation). Our data also explain why consecutive cortical UP states have uniform amplitudes in a given neuron. PMID:22934081

Visualization of Calcium Dynamics in Kidney Proximal Tubules

PubMed Central

Szebényi, Kornélia; Füredi, András; Kolacsek, Orsolya; Csohány, Rózsa; Prókai, Ágnes; Kis-Petik, Katalin; Szabó, Attila; Bősze, Zsuzsanna; Bender, Balázs; Tóvári, József; Enyedi, Ágnes; Orbán, Tamás I.

2015-01-01

Intrarenal changes in cytoplasmic calcium levels have a key role in determining pathologic and pharmacologic responses in major kidney diseases. However, cell-specific delivery of calcium-sensitive probes in vivo remains problematic. We generated a transgenic rat stably expressing the green fluorescent protein-calmodulin–based genetically encoded calcium indicator (GCaMP2) predominantly in the kidney proximal tubules. The transposon-based method used allowed the generation of homozygous transgenic rats containing one copy of the transgene per allele with a defined insertion pattern, without genetic or phenotypic alterations. We applied in vitro confocal and in vivo two-photon microscopy to examine basal calcium levels and ligand- and drug-induced alterations in these levels in proximal tubular epithelial cells. Notably, renal ischemia induced a transient increase in cellular calcium, and reperfusion resulted in a secondary calcium load, which was significantly decreased by systemic administration of specific blockers of the angiotensin receptor and the Na-Ca exchanger. The parallel examination of in vivo cellular calcium dynamics and renal circulation by fluorescent probes opens new possibilities for physiologic and pharmacologic investigations. PMID:25788535

A New Genetically Encoded Single-Chain Biosensor for Cdc42 Based on FRET, Useful for Live-Cell Imaging

PubMed Central

Cox, Dianne; Hodgson, Louis

2014-01-01

Cdc42 is critical in a myriad of cellular morphogenic processes, requiring precisely regulated activation dynamics to affect specific cellular events. To facilitate direct observations of Cdc42 activation in live cells, we developed and validated a new biosensor of Cdc42 activation. The biosensor is genetically encoded, of single-chain design and capable of correctly localizing to membrane compartments as well as interacting with its upstream regulators including the guanine nucleotide dissociation inhibitor. We characterized this new biosensor in motile mouse embryonic fibroblasts and observed robust activation dynamics at leading edge protrusions, similar to those previously observed for endogenous Cdc42 using the organic dye-based biosensor system. We then extended our validations and observations of Cdc42 activity to macrophages, and show that this new biosensor is able to detect differential activation patterns during phagocytosis and cytokine stimulation. Furthermore, we observe for the first time, a highly transient and localized activation of Cdc42 during podosome formation in macrophages, which was previously hypothesized but never directly visualized. PMID:24798463

A new genetically encoded single-chain biosensor for Cdc42 based on FRET, useful for live-cell imaging.

PubMed

Hanna, Samer; Miskolci, Veronika; Cox, Dianne; Hodgson, Louis

2014-01-01

Cdc42 is critical in a myriad of cellular morphogenic processes, requiring precisely regulated activation dynamics to affect specific cellular events. To facilitate direct observations of Cdc42 activation in live cells, we developed and validated a new biosensor of Cdc42 activation. The biosensor is genetically encoded, of single-chain design and capable of correctly localizing to membrane compartments as well as interacting with its upstream regulators including the guanine nucleotide dissociation inhibitor. We characterized this new biosensor in motile mouse embryonic fibroblasts and observed robust activation dynamics at leading edge protrusions, similar to those previously observed for endogenous Cdc42 using the organic dye-based biosensor system. We then extended our validations and observations of Cdc42 activity to macrophages, and show that this new biosensor is able to detect differential activation patterns during phagocytosis and cytokine stimulation. Furthermore, we observe for the first time, a highly transient and localized activation of Cdc42 during podosome formation in macrophages, which was previously hypothesized but never directly visualized.

Exploring space-time structure of human mobility in urban space

NASA Astrophysics Data System (ADS)

Sun, J. B.; Yuan, J.; Wang, Y.; Si, H. B.; Shan, X. M.

2011-03-01

Understanding of human mobility in urban space benefits the planning and provision of municipal facilities and services. Due to the high penetration of cell phones, mobile cellular networks provide information for urban dynamics with a large spatial extent and continuous temporal coverage in comparison with traditional approaches. The original data investigated in this paper were collected by cellular networks in a southern city of China, recording the population distribution by dividing the city into thousands of pixels. The space-time structure of urban dynamics is explored by applying Principal Component Analysis (PCA) to the original data, from temporal and spatial perspectives between which there is a dual relation. Based on the results of the analysis, we have discovered four underlying rules of urban dynamics: low intrinsic dimensionality, three categories of common patterns, dominance of periodic trends, and temporal stability. It implies that the space-time structure can be captured well by remarkably few temporal or spatial predictable periodic patterns, and the structure unearthed by PCA evolves stably over time. All these features play a critical role in the applications of forecasting and anomaly detection.

On the topological sensitivity of cellular automata

NASA Astrophysics Data System (ADS)

Baetens, Jan M.; De Baets, Bernard

2011-06-01

Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.

Watching cellular machinery in action, one molecule at a time.

PubMed

Monachino, Enrico; Spenkelink, Lisanne M; van Oijen, Antoine M

2017-01-02

Single-molecule manipulation and imaging techniques have become important elements of the biologist's toolkit to gain mechanistic insights into cellular processes. By removing ensemble averaging, single-molecule methods provide unique access to the dynamic behavior of biomolecules. Recently, the use of these approaches has expanded to the study of complex multiprotein systems and has enabled detailed characterization of the behavior of individual molecules inside living cells. In this review, we provide an overview of the various force- and fluorescence-based single-molecule methods with applications both in vitro and in vivo, highlighting these advances by describing their applications in studies on cytoskeletal motors and DNA replication. We also discuss how single-molecule approaches have increased our understanding of the dynamic behavior of complex multiprotein systems. These methods have shown that the behavior of multicomponent protein complexes is highly stochastic and less linear and deterministic than previously thought. Further development of single-molecule tools will help to elucidate the molecular dynamics of these complex systems both inside the cell and in solutions with purified components. © 2017 Monachino et al.

Quantifying the driving factors for language shift in a bilingual region

PubMed Central

Prochazka, Katharina; Vogl, Gero

2017-01-01

Many of the world’s around 6,000 languages are in danger of disappearing as people give up use of a minority language in favor of the majority language in a process called language shift. Language shift can be monitored on a large scale through the use of mathematical models by way of differential equations, for example, reaction–diffusion equations. Here, we use a different approach: we propose a model for language dynamics based on the principles of cellular automata/agent-based modeling and combine it with very detailed empirical data. Our model makes it possible to follow language dynamics over space and time, whereas existing models based on differential equations average over space and consequently provide no information on local changes in language use. Additionally, cellular automata models can be used even in cases where models based on differential equations are not applicable, for example, in situations where one language has become dispersed and retreated to language islands. Using data from a bilingual region in Austria, we show that the most important factor in determining the spread and retreat of a language is the interaction with speakers of the same language. External factors like bilingual schools or parish language have only a minor influence. PMID:28298530

Optical Antenna-Based Fluorescence Correlation Spectroscopy to Probe the Nanoscale Dynamics of Biological Membranes.

PubMed

Winkler, Pamina M; Regmi, Raju; Flauraud, Valentin; Brugger, Jürgen; Rigneault, Hervé; Wenger, Jérôme; García-Parajo, María F

2018-01-04

The plasma membrane of living cells is compartmentalized at multiple spatial scales ranging from the nano- to the mesoscale. This nonrandom organization is crucial for a large number of cellular functions. At the nanoscale, cell membranes organize into dynamic nanoassemblies enriched by cholesterol, sphingolipids, and certain types of proteins. Investigating these nanoassemblies known as lipid rafts is of paramount interest in fundamental cell biology. However, this goal requires simultaneous nanometer spatial precision and microsecond temporal resolution, which is beyond the reach of common microscopes. Optical antennas based on metallic nanostructures efficiently enhance and confine light into nanometer dimensions, breaching the diffraction limit of light. In this Perspective, we discuss recent progress combining optical antennas with fluorescence correlation spectroscopy (FCS) to monitor microsecond dynamics at nanoscale spatial dimensions. These new developments offer numerous opportunities to investigate lipid and protein dynamics in both mimetic and native biological membranes.

Modeling cell adhesion and proliferation: a cellular-automata based approach.

PubMed

Vivas, J; Garzón-Alvarado, D; Cerrolaza, M

Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.

The transition between immune and disease states in a cellular automaton model of clonal immune response

NASA Astrophysics Data System (ADS)

Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

1997-02-01

In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.

Global analysis of lysine acetylation in strawberry leaves.

PubMed

Fang, Xianping; Chen, Wenyue; Zhao, Yun; Ruan, Songlin; Zhang, Hengmu; Yan, Chengqi; Jin, Liang; Cao, Lingling; Zhu, Jun; Ma, Huasheng; Cheng, Zhongyi

2015-01-01

Protein lysine acetylation is a reversible and dynamic post-translational modification. It plays an important role in regulating diverse cellular processes including chromatin dynamic, metabolic pathways, and transcription in both prokaryotes and eukaryotes. Although studies of lysine acetylome in plants have been reported, the throughput was not high enough, hindering the deep understanding of lysine acetylation in plant physiology and pathology. In this study, taking advantages of anti-acetyllysine-based enrichment and high-sensitive-mass spectrometer, we applied an integrated proteomic approach to comprehensively investigate lysine acetylome in strawberry. In total, we identified 1392 acetylation sites in 684 proteins, representing the largest dataset of acetylome in plants to date. To reveal the functional impacts of lysine acetylation in strawberry, intensive bioinformatic analysis was performed. The results significantly expanded our current understanding of plant acetylome and demonstrated that lysine acetylation is involved in multiple cellular metabolism and cellular processes. More interestingly, nearly 50% of all acetylated proteins identified in this work were localized in chloroplast and the vital role of lysine acetylation in photosynthesis was also revealed. Taken together, this study not only established the most extensive lysine acetylome in plants to date, but also systematically suggests the significant and unique roles of lysine acetylation in plants.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

A Simple Microscopy Assay to Teach the Processes of Phagocytosis and Exocytosis

ERIC Educational Resources Information Center

Gray, Ross; Gray, Andrew; Fite, Jessica L.; Jordan, Renee; Stark, Sarah; Naylor, Kari

2012-01-01

Phagocytosis and exocytosis are two cellular processes involving membrane dynamics. While it is easy to understand the purpose of these processes, it can be extremely difficult for students to comprehend the actual mechanisms. As membrane dynamics play a significant role in many cellular processes ranging from cell signaling to cell division to…

Cellular and Network Mechanisms Underlying Information Processing in a Simple Sensory System

NASA Technical Reports Server (NTRS)

Jacobs, Gwen; Henze, Chris; Biegel, Bryan (Technical Monitor)

2002-01-01

Realistic, biophysically-based compartmental models were constructed of several primary sensory interneurons in the cricket cercal sensory system. A dynamic atlas of the afferent input to these cells was used to set spatio-temporal parameters for the simulated stimulus-dependent synaptic inputs. We examined the roles of dendritic morphology, passive membrane properties, and active conductances on the frequency tuning of the neurons. The sensitivity of narrow-band low pass interneurons could be explained entirely by the electronic structure of the dendritic arbors and the dynamic sensitivity of the SIZ. The dynamic characteristics of interneurons with higher frequency sensitivity required models with voltage-dependent dendritic conductances.

The Transcription Factor EB Links Cellular Stress to the Immune Response



PubMed Central

Nabar, Neel R.; Kehrl, John H.

2017-01-01

The transcription factor EB (TFEB) is the master transcriptional regulator of autophagy and lysosome biogenesis. Recent advances have led to a paradigm shift in our understanding of lysosomes from a housekeeping cellular waste bin to a dynamically regulated pathway that is efficiently turned up or down based on cellular needs. TFEB coordinates the cellular response to nutrient deprivation and other forms of cell stress through the lysosome system, and regulates a myriad of cellular processes associated with this system including endocytosis, phagocytosis, autophagy, and lysosomal exocytosis. Autophagy and the endolysosomal system are critical to both the innate and adaptive arms of the immune system, with functions in effector cell priming and direct pathogen clearance. Recent studies have linked TFEB to the regulation of the immune response through the endolysosmal pathway and by direct transcriptional activation of immune related genes. In this review, we discuss the current understanding of TFEB’s function and the molecular mechanisms behind TFEB activation. Finally, we discuss recent advances linking TFEB to the immune response that positions lysosomal signaling as a potential target for immune modulation. PMID:28656016

The Transcription Factor EB Links Cellular Stress to the Immune Response

.

PubMed

Nabar, Neel R; Kehrl, John H

2017-06-01

The transcription factor EB (TFEB) is the master transcriptional regulator of autophagy and lysosome biogenesis. Recent advances have led to a paradigm shift in our understanding of lysosomes from a housekeeping cellular waste bin to a dynamically regulated pathway that is efficiently turned up or down based on cellular needs. TFEB coordinates the cellular response to nutrient deprivation and other forms of cell stress through the lysosome system, and regulates a myriad of cellular processes associated with this system including endocytosis, phagocytosis, autophagy, and lysosomal exocytosis. Autophagy and the endolysosomal system are critical to both the innate and adaptive arms of the immune system, with functions in effector cell priming and direct pathogen clearance. Recent studies have linked TFEB to the regulation of the immune response through the endolysosmal pathway and by direct transcriptional activation of immune related genes. In this review, we discuss the current understanding of TFEB's function and the molecular mechanisms behind TFEB activation. Finally, we discuss recent advances linking TFEB to the immune response that positions lysosomal signaling as a potential target for immune modulation.

Role of cellular adhesions in tissue dynamics spectroscopy

NASA Astrophysics Data System (ADS)

Merrill, Daniel A.; An, Ran; Turek, John; Nolte, David

2014-02-01

Cellular adhesions play a critical role in cell behavior, and modified expression of cellular adhesion compounds has been linked to various cancers. We tested the role of cellular adhesions in drug response by studying three cellular culture models: three-dimensional tumor spheroids with well-developed cellular adhesions and extracellular matrix (ECM), dense three-dimensional cell pellets with moderate numbers of adhesions, and dilute three-dimensional cell suspensions in agarose having few adhesions. Our technique for measuring the drug response for the spheroids and cell pellets was biodynamic imaging (BDI), and for the suspensions was quasi-elastic light scattering (QELS). We tested several cytoskeletal chemotherapeutic drugs (nocodazole, cytochalasin-D, paclitaxel, and colchicine) on three cancer cell lines chosen from human colorectal adenocarcinoma (HT-29), human pancreatic carcinoma (MIA PaCa-2), and rat osteosarcoma (UMR-106) to exhibit differences in adhesion strength. Comparing tumor spheroid behavior to that of cell suspensions showed shifts in the spectral motion of the cancer tissues that match predictions based on different degrees of cell-cell contacts. The HT-29 cell line, which has the strongest adhesions in the spheroid model, exhibits anomalous behavior in some cases. These results highlight the importance of using three-dimensional tissue models in drug screening with cellular adhesions being a contributory factor in phenotypic differences between the drug responses of tissue and cells.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

Cellular reprogramming dynamics follow a simple 1D reaction coordinate

NASA Astrophysics Data System (ADS)

Teja Pusuluri, Sai; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2018-01-01

Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an ongoing problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple 1D reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of the experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges from epigenetic landscape models where cellular reprogramming is viewed as a ‘barrier-crossing’ process between cell fates. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an ‘optimal path’ in gene expression space for reprogramming.

Microscopic Imaging and Spectroscopy with Scattered Light

PubMed Central

Boustany, Nada N.; Boppart, Stephen A.; Backman, Vadim

2012-01-01

Optical contrast based on elastic scattering interactions between light and matter can be used to probe cellular structure and dynamics, and image tissue architecture. The quantitative nature and high sensitivity of light scattering signals to subtle alterations in tissue morphology, as well as the ability to visualize unstained tissue in vivo, has recently generated significant interest in optical scatter based biosensing and imaging. Here we review the fundamental methodologies used to acquire and interpret optical scatter data. We report on recent findings in this field and present current advances in optical scatter techniques and computational methods. Cellular and tissue data enabled by current advances in optical scatter spectroscopy and imaging stand to impact a variety of biomedical applications including clinical tissue diagnosis, in vivo imaging, drug discovery and basic cell biology. PMID:20617940

Understanding cellular architecture in cancer cells

NASA Astrophysics Data System (ADS)

Bianco, Simone; Tang, Chao

2011-03-01

Understanding the development of cancer is an important goal for today's science. The morphology of cellular organelles, such as the nucleus, the nucleoli and the mitochondria, which is referred to as cellular architecture or cytoarchitecture, is an important indicator of the state of the cell. In particular, there are striking difference between the cellular architecture of a healthy cell versus a cancer cell. In this work we present a dynamical model for the evolution of organelles morphology in cancer cells. Using a dynamical systems approach, we describe the evolution of a cell on its way to cancer as a trajectory in a multidimensional morphology state. The results provided by this work may increase our insight on the mechanism of tumorigenesis and help build new therapeutic strategies.

Endoplasmic Reticulum and the Unfolded Protein Response: Dynamics and Metabolic Integration

PubMed Central

Bravo, Roberto; Parra, Valentina; Gatica, Damián; Rodriguez, Andrea E.; Torrealba, Natalia; Paredes, Felipe; Wang, Zhao V.; Zorzano, Antonio; Hill, Joseph A.; Jaimovich, Enrique; Quest, Andrew F.G.; Lavandero, Sergio

2013-01-01

The endoplasmic reticulum (ER) is a dynamic intracellular organelle with multiple functions essential for cellular homeostasis, development, and stress responsiveness. In response to cellular stress, a well-established signaling cascade, the unfolded protein response (UPR), is activated. This intricate mechanism is an important means of reestablishing cellular homeostasis and alleviating the inciting stress. Now, emerging evidence has demonstrated that the UPR influences cellular metabolism through diverse mechanisms, including calcium and lipid transfer, raising the prospect of involvement of these processes in the pathogenesis of disease, including neurodegeneration, cancer, diabetes mellitus and cardiovascular disease. Here, we review the distinct functions of the ER and UPR from a metabolic point of view, highlighting their association with prevalent pathologies. PMID:23317820

Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information.

PubMed

Tack, Ignace L M M; Nimmegeers, Philippe; Akkermans, Simen; Hashem, Ihab; Van Impe, Jan F M

2017-01-01

Clustered microbial communities are omnipresent in the food industry, e.g., as colonies of microbial pathogens in/on food media or as biofilms on food processing surfaces. These clustered communities are often characterized by metabolic differentiation among their constituting cells as a result of heterogeneous environmental conditions in the cellular surroundings. This paper focuses on the role of metabolic differentiation due to oxygen gradients in the development of Escherichia coli cell communities, whereby low local oxygen concentrations lead to cellular secretion of weak acid products. For this reason, a metabolic model has been developed for the facultative anaerobe E. coli covering the range of aerobic, microaerobic, and anaerobic environmental conditions. This metabolic model is expressed as a multiparametric programming problem, in which the influence of low extracellular pH values and the presence of undissociated acid cell products in the environment has been taken into account. Furthermore, the developed metabolic model is incorporated in MICRODIMS, an in-house developed individual-based modeling framework to simulate microbial colony and biofilm dynamics. Two case studies have been elaborated using the MICRODIMS simulator: (i) biofilm growth on a substratum surface and (ii) submerged colony growth in a semi-solid mixed food product. In the first case study, the acidification of the biofilm environment and the emergence of typical biofilm morphologies have been observed, such as the mushroom-shaped structure of mature biofilms and the formation of cellular chains at the exterior surface of the biofilm. The simulations show that these morphological phenomena are respectively dependent on the initial affinity of pioneer cells for the substratum surface and the cell detachment process at the outer surface of the biofilm. In the second case study, a no-growth zone emerges in the colony center due to a local decline of the environmental pH. As a result, cellular growth in the submerged colony is limited to the colony periphery, implying a linear increase of the colony radius over time. MICRODIMS has been successfully used to reproduce complex dynamics of clustered microbial communities.

Using ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure

PubMed Central

Shah, Imran; Setzer, R. Woodrow; Jack, John; Houck, Keith A.; Judson, Richard S.; Knudsen, Thomas B.; Liu, Jie; Martin, Matthew T.; Reif, David M.; Richard, Ann M.; Thomas, Russell S.; Crofton, Kevin M.; Dix, David J.; Kavlock, Robert J.

2015-01-01

Background: High-content imaging (HCI) allows simultaneous measurement of multiple cellular phenotypic changes and is an important tool for evaluating the biological activity of chemicals. Objectives: Our goal was to analyze dynamic cellular changes using HCI to identify the “tipping point” at which the cells did not show recovery towards a normal phenotypic state. Methods: HCI was used to evaluate the effects of 967 chemicals (in concentrations ranging from 0.4 to 200 μM) on HepG2 cells over a 72-hr exposure period. The HCI end points included p53, c-Jun, histone H2A.x, α-tubulin, histone H3, alpha tubulin, mitochondrial membrane potential, mitochondrial mass, cell cycle arrest, nuclear size, and cell number. A computational model was developed to interpret HCI responses as cell-state trajectories. Results: Analysis of cell-state trajectories showed that 336 chemicals produced tipping points and that HepG2 cells were resilient to the effects of 334 chemicals up to the highest concentration (200 μM) and duration (72 hr) tested. Tipping points were identified as concentration-dependent transitions in system recovery, and the corresponding critical concentrations were generally between 5 and 15 times (25th and 75th percentiles, respectively) lower than the concentration that produced any significant effect on HepG2 cells. The remaining 297 chemicals require more data before they can be placed in either of these categories. Conclusions: These findings show the utility of HCI data for reconstructing cell state trajectories and provide insight into the adaptation and resilience of in vitro cellular systems based on tipping points. Cellular tipping points could be used to define a point of departure for risk-based prioritization of environmental chemicals. Citation: Shah I, Setzer RW, Jack J, Houck KA, Judson RS, Knudsen TB, Liu J, Martin MT, Reif DM, Richard AM, Thomas RS, Crofton KM, Dix DJ, Kavlock RJ. 2016. Using ToxCast™ data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure. Environ Health Perspect 124:910–919; http://dx.doi.org/10.1289/ehp.1409029 PMID:26473631

Hydrodynamic Determinants of Cell Necrosis and Molecular Delivery Produced by Pulsed Laser Microbeam Irradiation of Adherent Cells

PubMed Central

Compton, Jonathan L.; Hellman, Amy N.; Venugopalan, Vasan

2013-01-01

Time-resolved imaging, fluorescence microscopy, and hydrodynamic modeling were used to examine cell lysis and molecular delivery produced by picosecond and nanosecond pulsed laser microbeam irradiation in adherent cell cultures. Pulsed laser microbeam radiation at λ = 532 nm was delivered to confluent monolayers of PtK2 cells via a 40×, 0.8 NA microscope objective. Using laser microbeam pulse durations of 180–1100 ps and pulse energies of 0.5–10.5 μJ, we examined the resulting plasma formation and cavitation bubble dynamics that lead to laser-induced cell lysis, necrosis, and molecular delivery. The cavitation bubble dynamics are imaged at times of 0.5 ns to 50 μs after the pulsed laser microbeam irradiation, and fluorescence assays assess the resulting cell viability and molecular delivery of 3 kDa dextran molecules. Reductions in both the threshold laser microbeam pulse energy for plasma formation and the cavitation bubble energy are observed with decreasing pulse duration. These energy reductions provide for increased precision of laser-based cellular manipulation including cell lysis, cell necrosis, and molecular delivery. Hydrodynamic analysis reveals critical values for the shear-stress impulse generated by the cavitation bubble dynamics governs the location and spatial extent of cell necrosis and molecular delivery independent of pulse duration and pulse energy. Specifically, cellular exposure to a shear-stress impulse J≳0.1 Pa s ensures cell lysis or necrosis, whereas exposures in the range of 0.035≲J≲0.1 Pa s preserve cell viability while also enabling molecular delivery of 3 kDa dextran. Exposure to shear-stress impulses of J≲0.035 Pa s leaves the cells unaffected. Hydrodynamic analysis of these data, combined with data from studies of 6 ns microbeam irradiation, demonstrates the primacy of shear-stress impulse in determining cellular outcome resulting from pulsed laser microbeam irradiation spanning a nearly two-orders-of-magnitude range of pulse energy and pulse duration. These results provide a mechanistic foundation and design strategy applicable to a broad range of laser-based cellular manipulation procedures. PMID:24209868

Particle-based membrane model for mesoscopic simulation of cellular dynamics

NASA Astrophysics Data System (ADS)

Sadeghi, Mohsen; Weikl, Thomas R.; Noé, Frank

2018-01-01

We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.

A Hybrid Cellular Automaton Model of Clonal Evolution in Cancer: The Emergence of the Glycolytic Phenotype

PubMed Central

Gerlee, P.; Anderson, A.R.A.

2009-01-01

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. This implies that cells might react differently to the environment and when space and nutrients are limited only the fittest cells will survive. With this model we have investigated the impact of the environment on the growth dynamics of the tumour. In particular we have analysed the influence of the tissue oxygen concentration and extra-cellular matrix density on the dynamics of the model. We found that the environment influences both the growth and evolutionary dynamics of the tumour. For low oxygen concentration we observe tumours with a fingered morphology, while increasing the matrix density gives rise to more compact tumours with wider fingers. The distribution of phenotypes in the tumour is also affected, and we observe that the glycolytic phenotype is most likely to emerge in a poorly oxygenated tissue with a high matrix density. Our results suggest that it is the combined effect of the oxygen concentration and matrix density that creates an environment where the glycolytic phenotype has a growth advantage and consequently is most likely to appear. PMID:18068192

Laser-based direct-write techniques for cell printing

PubMed Central

Schiele, Nathan R; Corr, David T; Huang, Yong; Raof, Nurazhani Abdul; Xie, Yubing; Chrisey, Douglas B

2016-01-01

Fabrication of cellular constructs with spatial control of cell location (±5 μm) is essential to the advancement of a wide range of applications including tissue engineering, stem cell and cancer research. Precise cell placement, especially of multiple cell types in co- or multi-cultures and in three dimensions, can enable research possibilities otherwise impossible, such as the cell-by-cell assembly of complex cellular constructs. Laser-based direct writing, a printing technique first utilized in electronics applications, has been adapted to transfer living cells and other biological materials (e.g., enzymes, proteins and bioceramics). Many different cell types have been printed using laser-based direct writing, and this technique offers significant improvements when compared to conventional cell patterning techniques. The predominance of work to date has not been in application of the technique, but rather focused on demonstrating the ability of direct writing to pattern living cells, in a spatially precise manner, while maintaining cellular viability. This paper reviews laser-based additive direct-write techniques for cell printing, and the various cell types successfully laser direct-written that have applications in tissue engineering, stem cell and cancer research are highlighted. A particular focus is paid to process dynamics modeling and process-induced cell injury during laser-based cell direct writing. PMID:20814088

Systems microscopy: an emerging strategy for the life sciences.

PubMed

Lock, John G; Strömblad, Staffan

2010-05-01

Dynamic cellular processes occurring in time and space are fundamental to all physiology and disease. To understand complex and dynamic cellular processes therefore demands the capacity to record and integrate quantitative multiparametric data from the four spatiotemporal dimensions within which living cells self-organize, and to subsequently use these data for the mathematical modeling of cellular systems. To this end, a raft of complementary developments in automated fluorescence microscopy, cell microarray platforms, quantitative image analysis and data mining, combined with multivariate statistics and computational modeling, now coalesce to produce a new research strategy, "systems microscopy", which facilitates systems biology analyses of living cells. Systems microscopy provides the crucial capacities to simultaneously extract and interrogate multiparametric quantitative data at resolution levels ranging from the molecular to the cellular, thereby elucidating a more comprehensive and richly integrated understanding of complex and dynamic cellular systems. The unique capacities of systems microscopy suggest that it will become a vital cornerstone of systems biology, and here we describe the current status and future prospects of this emerging field, as well as outlining some of the key challenges that remain to be overcome. Copyright 2010 Elsevier Inc. All rights reserved.

Mitochondrial morphology transitions and functions: implications for retrograde signaling?

PubMed Central

Picard, Martin; Shirihai, Orian S.; Gentil, Benoit J.

2013-01-01

In response to cellular and environmental stresses, mitochondria undergo morphology transitions regulated by dynamic processes of membrane fusion and fission. These events of mitochondrial dynamics are central regulators of cellular activity, but the mechanisms linking mitochondrial shape to cell function remain unclear. One possibility evaluated in this review is that mitochondrial morphological transitions (from elongated to fragmented, and vice-versa) directly modify canonical aspects of the organelle's function, including susceptibility to mitochondrial permeability transition, respiratory properties of the electron transport chain, and reactive oxygen species production. Because outputs derived from mitochondrial metabolism are linked to defined cellular signaling pathways, fusion/fission morphology transitions could regulate mitochondrial function and retrograde signaling. This is hypothesized to provide a dynamic interface between the cell, its genome, and the fluctuating metabolic environment. PMID:23364527

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is further concluded that in most social simulation settings the Agent-based modeling approach would be the probable choice. This since the other models does not offer much in the way of supporting the modeling of the anticipatory behavior of humans acting in an organization.

Distal gap junctions and active dendrites can tune network dynamics.

PubMed

Saraga, Fernanda; Ng, Leo; Skinner, Frances K

2006-03-01

Gap junctions allow direct electrical communication between CNS neurons. From theoretical and modeling studies, it is well known that although gap junctions can act to synchronize network output, they can also give rise to many other dynamic patterns including antiphase and other phase-locked states. The particular network pattern that arises depends on cellular, intrinsic properties that affect firing frequencies as well as the strength and location of the gap junctions. Interneurons or GABAergic neurons in hippocampus are diverse in their cellular characteristics and have been shown to have active dendrites. Furthermore, parvalbumin-positive GABAergic neurons, also known as basket cells, can contact one another via gap junctions on their distal dendrites. Using two-cell network models, we explore how distal electrical connections affect network output. We build multi-compartment models of hippocampal basket cells using NEURON and endow them with varying amounts of active dendrites. Two-cell networks of these model cells as well as reduced versions are explored. The relationship between intrinsic frequency and the level of active dendrites allows us to define three regions based on what sort of network dynamics occur with distal gap junction coupling. Weak coupling theory is used to predict the delineation of these regions as well as examination of phase response curves and distal dendritic polarization levels. We find that a nonmonotonic dependence of network dynamic characteristics (phase lags) on gap junction conductance occurs. This suggests that distal electrical coupling and active dendrite levels can control how sensitive network dynamics are to gap junction modulation. With the extended geometry, gap junctions located at more distal locations must have larger conductances for pure synchrony to occur. Furthermore, based on simulations with heterogeneous networks, it may be that one requires active dendrites if phase-locking is to occur in networks formed with distal gap junctions.

Imaging C. elegans embryos using an epifluorescent microscope and open source software.

PubMed

Verbrugghe, Koen J C; Chan, Raymond C

2011-03-24

Cellular processes, such as chromosome assembly, segregation and cytokinesis,are inherently dynamic. Time-lapse imaging of living cells, using fluorescent-labeled reporter proteins or differential interference contrast (DIC) microscopy, allows for the examination of the temporal progression of these dynamic events which is otherwise inferred from analysis of fixed samples(1,2). Moreover, the study of the developmental regulations of cellular processes necessitates conducting time-lapse experiments on an intact organism during development. The Caenorhabiditis elegans embryo is light-transparent and has a rapid, invariant developmental program with a known cell lineage(3), thus providing an ideal experiment model for studying questions in cell biology(4,5)and development(6-9). C. elegans is amendable to genetic manipulation by forward genetics (based on random mutagenesis(10,11)) and reverse genetics to target specific genes (based on RNAi-mediated interference and targeted mutagenesis(12-15)). In addition, transgenic animals can be readily created to express fluorescently tagged proteins or reporters(16,17). These traits combine to make it easy to identify the genetic pathways regulating fundamental cellular and developmental processes in vivo(18-21). In this protocol we present methods for live imaging of C. elegans embryos using DIC optics or GFP fluorescence on a compound epifluorescent microscope. We demonstrate the ease with which readily available microscopes, typically used for fixed sample imaging, can also be applied for time-lapse analysis using open-source software to automate the imaging process.

Matrix remodeling between cells and cellular interactions with collagen bundle

NASA Astrophysics Data System (ADS)

Kim, Jihan; Sun, Bo

When cells are surrounded by complex environment, they continuously probe and interact with it by applying cellular traction forces. As cells apply traction forces, they can sense rigidity of their local environment and remodel the matrix microstructure simultaneously. Previous study shows that single human carcinoma cell (MDA-MB-231) remodeled its surrounding extracellular matrix (ECM) and the matrix remodeling was reversible. In this study we examined the matrix microstructure between cells and cellular interaction between them using quantitative confocal microscopy. The result shows that the matrix microstructure is the most significantly remodeled between cells consisting of aligned, and densified collagen fibers (collagen bundle)., the result shows that collagen bundle is irreversible and significantly change micromechanics of ECM around the bundle. We further examined cellular interaction with collagen bundle by analyzing dynamics of actin and talin formation along with the direction of bundle. Lastly, we analyzed dynamics of cellular protrusion and migrating direction of cells along the bundle.

Dynamic interactions between 14-3-3 proteins and phosphoproteins regulate diverse cellular processes

PubMed Central

2004-01-01

14-3-3 proteins exert an extraordinarily widespread influence on cellular processes in all eukaryotes. They operate by binding to specific phosphorylated sites on diverse target proteins, thereby forcing conformational changes or influencing interactions between their targets and other molecules. In these ways, 14-3-3s ‘finish the job’ when phosphorylation alone lacks the power to drive changes in the activities of intracellular proteins. By interacting dynamically with phosphorylated proteins, 14-3-3s often trigger events that promote cell survival – in situations from preventing metabolic imbalances caused by sudden darkness in leaves to mammalian cell-survival responses to growth factors. Recent work linking specific 14-3-3 isoforms to genetic disorders and cancers, and the cellular effects of 14-3-3 agonists and antagonists, indicate that the cellular complement of 14-3-3 proteins may integrate the specificity and strength of signalling through to different cellular responses. PMID:15167810

Validation of the Dynamic Direct Exposure Method for Toxicity Testing of Diesel Exhaust In Vitro

PubMed Central

Hayes, Amanda; Bakand, Shahnaz

2013-01-01

Diesel exhaust emission is a major health concern because of the complex nature of its gaseous content (e.g., NO2, NO, CO, and CO2) and high concentration of particulate matter (PM) less than 2.5 μm which allows for deeper penetration into the human pulmonary system upon inhalation. The aim of this research was to elucidate the potential toxic effects of diesel exhaust on a human pulmonary-based cellular system. Validation of a dynamic direct exposure method for both laboratory (230 hp Volvo truck engine) and field (Volkswagen Passat passenger car) diesel engines, at idle mode, was implemented. Human pulmonary type II epithelial cells (A549) grown on porous membranes were exposed to unmodified diesel exhaust at a low flow rate (37.5 mL/min). In parallel, diesel emission sampling was also conducted using real-time air monitoring techniques. Induced cellular effects were assessed using a range of in vitro cytotoxicity assays (MTS, ATP, and NRU). Reduction of cell viability was observed in a time-dependent manner following 30–60 mins of exposure with NRU as the most sensitive assay. The results suggest that the dynamic direct exposure method has the potential to be implemented for both laboratory- and field-based in vitro toxicity studies of diesel exhaust emissions. PMID:23986878

Quantitative phase microscopy for cellular dynamics based on transport of intensity equation.

PubMed

Li, Ying; Di, Jianglei; Ma, Chaojie; Zhang, Jiwei; Zhong, Jinzhan; Wang, Kaiqiang; Xi, Teli; Zhao, Jianlin

2018-01-08

We demonstrate a simple method for quantitative phase imaging of tiny transparent objects such as living cells based on the transport of intensity equation. The experiments are performed using an inverted bright field microscope upgraded with a flipping imaging module, which enables to simultaneously create two laterally separated images with unequal defocus distances. This add-on module does not include any lenses or gratings and is cost-effective and easy-to-alignment. The validity of this method is confirmed by the measurement of microlens array and human osteoblastic cells in culture, indicating its potential in the applications of dynamically measuring living cells and other transparent specimens in a quantitative, non-invasive and label-free manner.

Spatial and temporal dynamics of receptor for advanced glycation endproducts, integrins, and actin cytoskeleton as probed with fluorescence-based imaging techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Syed, Aleem

Systematic spatial and temporal fluctuations are a fundamental part of any biological process. For example, lateral diffusion of membrane proteins is one of the key mechanisms in their cellular function. Lateral diffusion governs how membrane proteins interact with intracellular, transmembrane, and extracellular components to achieve their function. Herein, fluorescence-based techniques are used to elucidate the dynamics of receptor for advanced glycation end-products (RAGE) and integrin membrane proteins. RAGE is a transmembrane protein that is being used as a biomarker for various diseases. RAGE dependent signaling in numerous pathological conditions is well studied. However, RAGE lateral diffusion in the cell membranemore » is poorly understood. For this purpose, effect of cholesterol, cytoskeleton dynamics, and presence of ligand on RAGE lateral diffusion is investigated.« less

Inferring Time-Varying Network Topologies from Gene Expression Data

PubMed Central

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster—to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence. PMID:18309363

Inferring time-varying network topologies from gene expression data.

PubMed

Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

Size and surface functionalization of iron oxide nanoparticles influence the composition and dynamic nature of their protein corona.

PubMed

Ashby, Jonathan; Pan, Songqin; Zhong, Wenwan

2014-09-10

Nanoparticles (NPs) adsorb proteins when in the biological matrix, and the resulted protein corona could affect NP-cell interactions. The corona has a dynamic nature with the adsorbed proteins constantly exchanging with the free proteins in the matrix at various rates. The rapidly exchanging proteins compose the soft corona, which responds more dynamically to environment changes than the hard corona established by the ones with slow exchange rates. In the present study, the corona formed on the superparamagnetic iron oxide NPs (SPIONs) in human serum was studied by flow field-flow fractionation and ultracentrifugation, which rapidly differentiated the corona proteins based on their exchange rates. By varying the surface hydrophobicity of the SPIONs with a core size around 10 nm, we found out that, the more hydrophobic surface ligand attracted proteins with higher surface hydrophobicity and formed a more dynamic corona with a larger portion of the involved proteins with fast exchange rates. Increasing the core diameter of the SPIONs but keeping the surface ligand the same could also result in a more dynamic corona. A brief investigation of the effect on the cellular uptake of SPIONs using one selected corona protein, transferrin, was conducted. The result showed that, only the stably bound transferrin could significantly enhance cellular uptake, while transferrin bound in a dynamic nature had negligible impact. Our study has led to a better understanding of the relationship between the particle properties and the dynamic nature of the corona, which can help with design of nanomaterials with higher biocompatibility and higher efficacy in biosystems for biomedical applications.

Size and Surface Functionalization of Iron Oxide Nanoparticles Influence the Composition and Dynamic Nature of Their Protein Corona

PubMed Central

2015-01-01

Nanoparticles (NPs) adsorb proteins when in the biological matrix, and the resulted protein corona could affect NP-cell interactions. The corona has a dynamic nature with the adsorbed proteins constantly exchanging with the free proteins in the matrix at various rates. The rapidly exchanging proteins compose the soft corona, which responds more dynamically to environment changes than the hard corona established by the ones with slow exchange rates. In the present study, the corona formed on the superparamagnetic iron oxide NPs (SPIONs) in human serum was studied by flow field-flow fractionation and ultracentrifugation, which rapidly differentiated the corona proteins based on their exchange rates. By varying the surface hydrophobicity of the SPIONs with a core size around 10 nm, we found out that, the more hydrophobic surface ligand attracted proteins with higher surface hydrophobicity and formed a more dynamic corona with a larger portion of the involved proteins with fast exchange rates. Increasing the core diameter of the SPIONs but keeping the surface ligand the same could also result in a more dynamic corona. A brief investigation of the effect on the cellular uptake of SPIONs using one selected corona protein, transferrin, was conducted. The result showed that, only the stably bound transferrin could significantly enhance cellular uptake, while transferrin bound in a dynamic nature had negligible impact. Our study has led to a better understanding of the relationship between the particle properties and the dynamic nature of the corona, which can help with design of nanomaterials with higher biocompatibility and higher efficacy in biosystems for biomedical applications. PMID:25144382

From the Cover: Visualization of maltose uptake in living yeast cells by fluorescent nanosensors

NASA Astrophysics Data System (ADS)

Fehr, Marcus; Frommer, Wolf B.; Lalonde, Sylvie

2002-07-01

Compartmentation of metabolic reactions and thus transport within and between cells can be understood only if we know subcellular distribution based on nondestructive dynamic monitoring. Currently, methods are not available for in vivo metabolite imaging at cellular or subcellular levels. Limited information derives from methods requiring fixation or fractionation of tissue (1, 2). We thus developed a flexible strategy for designing protein-based nanosensors for a wide spectrum of solutes, allowing analysis of changes in solute concentration in living cells. We made use of bacterial periplasmic binding proteins (PBPs), where we show that, on binding of the substrate, PBPs transform their hinge-bend movement into increased fluorescence resonance energy transfer (FRET) between two coupled green fluorescent proteins. By using the maltose-binding protein as a prototype, nanosensors were constructed allowing in vitro determination of FRET changes in a concentration-dependent fashion. For physiological applications, mutants with different binding affinities were generated, allowing dynamic in vivo imaging of the increase in cytosolic maltose concentration in single yeast cells. Control sensors allow the exclusion of the effect from other cellular or environmental parameters on ratio imaging. Thus the myriad of PBPs recognizing a wide spectrum of different substrates is suitable for FRET-based in vivo detection, providing numerous scientific, medical, and environmental applications.

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

DOE PAGES

Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe; ...

2017-04-07

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

Studying of cellular interaction of hairpin-like peptide EcAMP1 from barnyard grass (Echinochloa crusgalli L.) seeds with plant pathogenic fungus Fusarium solani using microscopy techniques.

PubMed

Vasilchenko, Alexey S; Yuryev, Mikhail; Ryazantsev, Dmitry Yu; Zavriev, Sergey K; Feofanov, Alexey V; Grishin, Eugene V; Rogozhin, Eugene A

2016-11-01

An interaction of recombinant hairpin-like cationic peptide EcAMP1 with conidia of plant pathogenic fungus Fusarium solani at the cellular level was studied by a combination of microscopic methods. EcAMP1 is from barnyard grass (Echinochloa crusgalli L.), and obtained by heterologous expression in Escherichia coli system. As a result, a direct relationship between hyphal growth inhibition and increasing active peptide concentration, time of incubation and fungal physiological condition has been determined. Dynamics of accumulation and redistribution of the peptide studied on fungal cellular cover and inside the conidia cells has been shown. The dynamics are dependent on time of coupling, as well as, a dissimilarity of EcAMP1 binding with cover of fungal conidia and its stepwise accumulation and diffuse localization in the cytoplasm. Correlation between structural disruption of fungal conidia and the presence of morphological changes has also been found. The correlation was found under the influence of peptide high concentrations at concentrations above 32 μM. The results indicate the presence of a binding of EcAMP1 with the surface of fungal conidia, thus, demonstrating a main specificity for its antifungal action at the cellular level. These results, however, cannot exclude the existence of attendant EcAMP1 action based on its intracellular localization on some specific targets. SCANNING 38:591-598, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Temporal Expression-based Analysis of Metabolism

PubMed Central

Segrè, Daniel

2012-01-01

Metabolic flux is frequently rerouted through cellular metabolism in response to dynamic changes in the intra- and extra-cellular environment. Capturing the mechanisms underlying these metabolic transitions in quantitative and predictive models is a prominent challenge in systems biology. Progress in this regard has been made by integrating high-throughput gene expression data into genome-scale stoichiometric models of metabolism. Here, we extend previous approaches to perform a Temporal Expression-based Analysis of Metabolism (TEAM). We apply TEAM to understanding the complex metabolic dynamics of the respiratorily versatile bacterium Shewanella oneidensis grown under aerobic, lactate-limited conditions. TEAM predicts temporal metabolic flux distributions using time-series gene expression data. Increased predictive power is achieved by supplementing these data with a large reference compendium of gene expression, which allows us to take into account the unique character of the distribution of expression of each individual gene. We further propose a straightforward method for studying the sensitivity of TEAM to changes in its fundamental free threshold parameter θ, and reveal that discrete zones of distinct metabolic behavior arise as this parameter is changed. By comparing the qualitative characteristics of these zones to additional experimental data, we are able to constrain the range of θ to a small, well-defined interval. In parallel, the sensitivity analysis reveals the inherently difficult nature of dynamic metabolic flux modeling: small errors early in the simulation propagate to relatively large changes later in the simulation. We expect that handling such “history-dependent” sensitivities will be a major challenge in the future development of dynamic metabolic-modeling techniques. PMID:23209390

In situ sensing and modeling of molecular events at the cellular level

NASA Astrophysics Data System (ADS)

Yang, Ruiguo

We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that were revealed by flow cytometry. The model would then be able to decipher qualitatively the molecular dynamics infolded in the regulation of cell behavior. To decipher the signaling pathway quantitatively, we employed a nanomechanical sensor at the bottom of the cell, quartz crystal microbalance with energy dissipation monitoring (QCM-D) to monitor the change at the basal area of the cell. This would provide the real time focal adhesion information and would be used in accordance with the AFM measurement data on the top of the cell to build a more complete mechanical profile during the antibody induced signaling process. We developed a model from a systematic control perspective that considers the signaling cascade at certain stimulation as the controller and the mechanical and structural interaction of the cell as the plant. We firstly derived the plant model based on QCM-D and AFM measurement processes. A signaling pathway model was built on a grey box approach where part of the pathway map was delineated in detail while others were condensed into a single reaction. The model parameters were obtained by extracting the mechanical response from the experiment. The model refinements were conducted by testing a series of inhibition mechanisms and comparing the simulation data with the experimental data. The model was then used to predict the existences of certain reactions that are qualitatively reported in the literature.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

PubMed

Brocklehurst, Paul; Ni, Haibo; Zhang, Henggui; Ye, Jianqiao

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue

PubMed Central

Zhang, Henggui

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation. PMID:28510575

Computation Modeling of Limb-bud Dysmorphogenesis: Predicting Cellular Dynamics and Key Events in Developmental Toxicity with a Multicellular Systems Model (FutureToxII)

EPA Science Inventory

Congenital limb malformations are among the most frequent malformation occurs in humans, with a frequency of about 1 in 500 to 1 in 1000 human live births. ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput (HTS) and computational methods that...

Tracking transcriptional activities with high-content epifluorescent imaging

NASA Astrophysics Data System (ADS)

Hua, Jianping; Sima, Chao; Cypert, Milana; Gooden, Gerald C.; Shack, Sonsoles; Alla, Lalitamba; Smith, Edward A.; Trent, Jeffrey M.; Dougherty, Edward R.; Bittner, Michael L.

2012-04-01

High-content cell imaging based on fluorescent protein reporters has recently been used to track the transcriptional activities of multiple genes under different external stimuli for extended periods. This technology enhances our ability to discover treatment-induced regulatory mechanisms, temporally order their onsets and recognize their relationships. To fully realize these possibilities and explore their potential in biological and pharmaceutical applications, we introduce a new data processing procedure to extract information about the dynamics of cell processes based on this technology. The proposed procedure contains two parts: (1) image processing, where the fluorescent images are processed to identify individual cells and allow their transcriptional activity levels to be quantified; and (2) data representation, where the extracted time course data are summarized and represented in a way that facilitates efficient evaluation. Experiments show that the proposed procedure achieves fast and robust image segmentation with sufficient accuracy. The extracted cellular dynamics are highly reproducible and sensitive enough to detect subtle activity differences and identify mechanisms responding to selected perturbations. This method should be able to help biologists identify the alterations of cellular mechanisms that allow drug candidates to change cell behavior and thereby improve the efficiency of drug discovery and treatment design.

Dynamic microvesicle release and clearance within the cardiovascular system: triggers and mechanisms.

PubMed

Ayers, Lisa; Nieuwland, Rienk; Kohler, Malcolm; Kraenkel, Nicolle; Ferry, Berne; Leeson, Paul

2015-12-01

Interest in cell-derived microvesicles (or microparticles) within cardiovascular diagnostics and therapeutics is rapidly growing. Microvesicles are often measured in the circulation at a single time point. However, it is becoming clear that microvesicle levels both increase and decrease rapidly in response to certain stimuli such as hypoxia, acute cardiac stress, shear stress, hypertriglyceridaemia and inflammation. Consequently, the levels of circulating microvesicles will reflect the balance between dynamic mechanisms for release and clearance. The present review describes the range of triggers currently known to lead to microvesicle release from different cellular origins into the circulation. Specifically, the published data are used to summarize the dynamic impact of these triggers on the degree and rate of microvesicle release. Secondly, a summary of the current understanding of microvesicle clearance via different cellular systems, including the endothelial cell and macrophage, is presented, based on reported studies of clearance in experimental models and clinical scenarios, such as transfusion or cardiac stress. Together, this information can be used to provide insights into potential underlying biological mechanisms that might explain the increases or decreases in circulating microvesicle levels that have been reported and help to design future clinical studies. © 2015 Authors; published by Portland Press Limited.

Guided by curvature: shaping cells by coupling curved membrane proteins and cytoskeletal forces.

PubMed

Gov, N S

2018-05-26

Eukaryote cells have flexible membranes that allow them to have a variety of dynamical shapes. The shapes of the cells serve important biological functions, both for cells within an intact tissue, and during embryogenesis and cellular motility. How cells control their shapes and the structures that they form on their surface has been a subject of intensive biological research, exposing the building blocks that cells use to deform their membranes. These processes have also drawn the interest of theoretical physicists, aiming to develop models based on physics, chemistry and nonlinear dynamics. Such models explore quantitatively different possible mechanisms that the cells can employ to initiate the spontaneous formation of shapes and patterns on their membranes. We review here theoretical work where one such class of mechanisms was investigated: the coupling between curved membrane proteins, and the cytoskeletal forces that they recruit. Theory indicates that this coupling gives rise to a rich variety of membrane shapes and dynamics, while experiments indicate that this mechanism appears to drive many cellular shape changes.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Nonlinear dynamics of C-terminal tails in cellular microtubules

NASA Astrophysics Data System (ADS)

Sekulic, Dalibor L.; Sataric, Bogdan M.; Zdravkovic, Slobodan; Bugay, Aleksandr N.; Sataric, Miljko V.

2016-07-01

The mechanical and electrical properties, and information processing capabilities of microtubules are the permanent subject of interest for carrying out experiments in vitro and in silico, as well as for theoretical attempts to elucidate the underlying processes. In this paper, we developed a new model of the mechano-electrical waves elicited in the rows of very flexible C-terminal tails which decorate the outer surface of each microtubule. The fact that C-terminal tails play very diverse roles in many cellular functions, such as recruitment of motor proteins and microtubule-associated proteins, motivated us to consider their collective dynamics as the source of localized waves aimed for communication between microtubule and associated proteins. Our approach is based on the ferroelectric liquid crystal model and it leads to the effective asymmetric double-well potential which brings about the conditions for the appearance of kink-waves conducted by intrinsic electric fields embedded in microtubules. These kinks can serve as the signals for control and regulation of intracellular traffic along microtubules performed by processive motions of motor proteins, primarly from kinesin and dynein families. On the other hand, they can be precursors for initiation of dynamical instability of microtubules by recruiting the proper proteins responsible for the depolymerization process.

Reversible RNA adenosine methylation in biological regulation

PubMed Central

Jia, Guifang; Fu, Ye; He, Chuan

2012-01-01

N6-methyladenosine (m6A) is a ubiquitous modification in messenger RNA (mRNA) and other RNAs across most eukaryotes. For many years, however, the exact functions of m6A were not clearly understood. The discovery that the fat mass and obesity associated protein (FTO) is an m6A demethylase indicates that this modification is reversible and dynamically regulated, suggesting it has regulatory roles. In addition, it has been shown that m6A affects cell fate decisions in yeast and plant development. Recent affinity-based m6A profiling in mouse and human cells further showed that this modification is a widespread mark in coding and non-coding RNA transcripts and is likely dynamically regulated throughout developmental processes. Therefore, reversible RNA methylation, analogous to reversible DNA and histone modifications, may affect gene expression and cell fate decisions by modulating multiple RNA-related cellular pathways, which potentially provides rapid responses to various cellular and environmental signals, including energy and nutrient availability in mammals. PMID:23218460

A reconfigurable visual-programming library for real-time closed-loop cellular electrophysiology

PubMed Central

Biró, István; Giugliano, Michele

2015-01-01

Most of the software platforms for cellular electrophysiology are limited in terms of flexibility, hardware support, ease of use, or re-configuration and adaptation for non-expert users. Moreover, advanced experimental protocols requiring real-time closed-loop operation to investigate excitability, plasticity, dynamics, are largely inaccessible to users without moderate to substantial computer proficiency. Here we present an approach based on MATLAB/Simulink, exploiting the benefits of LEGO-like visual programming and configuration, combined to a small, but easily extendible library of functional software components. We provide and validate several examples, implementing conventional and more sophisticated experimental protocols such as dynamic-clamp or the combined use of intracellular and extracellular methods, involving closed-loop real-time control. The functionality of each of these examples is demonstrated with relevant experiments. These can be used as a starting point to create and support a larger variety of electrophysiological tools and methods, hopefully extending the range of default techniques and protocols currently employed in experimental labs across the world. PMID:26157385

Chemoproteomics Reveals Chemical Diversity and Dynamics of 4-Oxo-2-nonenal Modifications in Cells.

PubMed

Sun, Rui; Fu, Ling; Liu, Keke; Tian, Caiping; Yang, Yong; Tallman, Keri A; Porter, Ned A; Liebler, Daniel C; Yang, Jing

2017-10-01

4-Oxo-2-nonenal (ONE) derived from lipid peroxidation modifies nucleophiles and transduces redox signaling by its reactions with proteins. However, the molecular interactions between ONE and complex proteomes and their dynamics in situ remain largely unknown. Here we describe a quantitative chemoproteomic analysis of protein adduction by ONE in cells, in which the cellular target profile of ONE is mimicked by its alkynyl surrogate. The analyses reveal four types of ONE-derived modifications in cells, including ketoamide and Schiff-base adducts to lysine, Michael adducts to cysteine, and a novel pyrrole adduct to cysteine. ONE-derived adducts co-localize and exhibit crosstalk with many histone marks and redox sensitive sites. All four types of modifications derived from ONE can be reversed site-specifically in cells. Taken together, our study provides much-needed mechanistic insights into the cellular signaling and potential toxicities associated with this important lipid derived electrophile. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Ubiquitination dynamics in the early-branching eukaryote Giardia intestinalis

PubMed Central

Niño, Carlos A; Chaparro, Jenny; Soffientini, Paolo; Polo, Simona; Wasserman, Moises

2013-01-01

Ubiquitination is a highly dynamic and versatile posttranslational modification that regulates protein function, stability, and interactions. To investigate the roles of ubiquitination in a primitive eukaryotic lineage, we utilized the early-branching eukaryote Giardia intestinalis. Using a combination of biochemical, immunofluorescence-based, and proteomics approaches, we assessed the ubiquitination status during the process of differentiation in Giardia. We observed that different types of ubiquitin modifications present specific cellular and temporal distribution throughout the Giardia life cycle from trophozoites to cyst maturation. Ubiquitin signal was detected in the wall of mature cysts, and enzymes implicated in cyst wall biogenesis were identified as substrates for ubiquitination. Interestingly, inhibition of proteasome activity did not affect trophozoite replication and differentiation, while it caused a decrease in cyst viability, arguing for proteasome involvement in cyst wall maturation. Using a proteomics approach, we identified around 200 high-confidence ubiquitinated candidates that vary their ubiquitination status during differentiation. Our results indicate that ubiquitination is critical for several cellular processes in this primitive eukaryote. PMID:23613346

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio

2013-10-01

We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.

Cellular Responses to Mechanical Stress Selected Contribution: A Three-Dimensional Model for Assessment of in Vitro Toxicity in Balaena Mysticetus Renal Tissue

NASA Technical Reports Server (NTRS)

Goodwin, T. J.; Coate-Li, L.; Linnehan, R. M.; Hammond, T. G.

2000-01-01

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.

Integrating Cellular Metabolism into a Multiscale Whole-Body Model

PubMed Central

Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

2012-01-01

Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

Dengue fever spreading based on probabilistic cellular automata with two lattices

NASA Astrophysics Data System (ADS)

Pereira, F. M. M.; Schimit, P. H. T.

2018-06-01

Modeling and simulation of mosquito-borne diseases have gained attention due to a growing incidence in tropical countries in the past few years. Here, we study the dengue spreading in a population modeled by cellular automata, where there are two lattices to model the human-mosquitointeraction: one lattice for human individuals, and one lattice for mosquitoes in order to enable different dynamics in populations. The disease considered is the dengue fever with one, two or three different serotypes coexisting in population. Although many regions exhibit the incidence of only one serotype, here we set a complete framework to also study the occurrence of two and three serotypes at the same time in a population. Furthermore, the flexibility of the model allows its use to other mosquito-borne diseases, like chikungunya, yellow fever and malaria. An approximation of the cellular automata is proposed in terms of ordinary differential equations; the spreading of mosquitoes is studied and the influence of some model parameters are analyzed with numerical simulations. Finally, a method to combat dengue spreading is simulated based on a reduction of mosquito birth and mosquito bites in population.

Interrogation of Cellular Innate Immunity by Diamond-Nanoneedle-Assisted Intracellular Molecular Fishing.

PubMed

Wang, Zixun; Yang, Yang; Xu, Zhen; Wang, Ying; Zhang, Wenjun; Shi, Peng

2015-10-14

Understanding intracellular signaling cascades and network is one of the core topics in modern biology. Novel tools based on nanotechnologies have enabled probing and analyzing intracellular signaling with unprecedented sensitivity and specificity. In this study, we developed a minimally invasive method for in situ probing specific signaling components of cellular innate immunity in living cells. The technique was based on diamond-nanoneedle arrays functionalized with aptamer-based molecular sensors, which were inserted into cytoplasmic domain using a centrifugation controlled process to capture molecular targets. Simultaneously, these diamond-nanoneedles also facilitated the delivery of double-strand DNAs (dsDNA90) into cells to activate the pathway involving the stimulator of interferon genes (STING). We showed that the nanoneedle-based biosensors can be successfully utilized to isolate transcriptional factor, NF-κB, from intracellular regions without damaging the cells, upon STING activation. By using a reversible protocol and repeated probing in living cells, we were able to examine the singling dynamics of NF-κB, which was quickly translocated from cytoplasm to nucleus region within ∼40 min of intracellular introduction of dsDNA90 for both A549 and neuron cells. These results demonstrated a novel and versatile tool for targeted in situ dissection of intracellular signaling, providing the potential to resolve new sights into various cellular processes.

Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution.

PubMed

Knowles, David W; Biggin, Mark D

2013-01-01

Animals comprise dynamic three-dimensional arrays of cells that express gene products in intricate spatial and temporal patterns that determine cellular differentiation and morphogenesis. A rigorous understanding of these developmental processes requires automated methods that quantitatively record and analyze complex morphologies and their associated patterns of gene expression at cellular resolution. Here we summarize light microscopy-based approaches to establish permanent, quantitative datasets-atlases-that record this information. We focus on experiments that capture data for whole embryos or large areas of tissue in three dimensions, often at multiple time points. We compare and contrast the advantages and limitations of different methods and highlight some of the discoveries made. We emphasize the need for interdisciplinary collaborations and integrated experimental pipelines that link sample preparation, image acquisition, image analysis, database design, visualization, and quantitative analysis. Copyright © 2013 Wiley Periodicals, Inc.

Lab-On-Chip Clinorotation System for Live-Cell Microscopy Under Simulated Microgravity

NASA Technical Reports Server (NTRS)

Yew, Alvin G.; Atencia, Javier; Chinn, Ben; Hsieh, Adam H.

2013-01-01

Cells in microgravity are subject to mechanical unloading and changes to the surrounding chemical environment. How these factors jointly influence cellular function is not well understood. We can investigate their role using ground-based analogues to spaceflight, where mechanical unloading is simulated through the time-averaged nullification of gravity. The prevailing method for cellular microgravity simulation is to use fluid-filled containers called clinostats. However, conventional clinostats are not designed for temporally tracking cell response, nor are they able to establish dynamic fluid environments. To address these needs, we developed a Clinorotation Time-lapse Microscopy (CTM) system that accommodates lab-on- chip cell culture devices for visualizing time-dependent alterations to cellular behavior. For the purpose of demonstrating CTM, we present preliminary results showing time-dependent differences in cell area between human mesenchymal stem cells (hMSCs) under modeled microgravity and normal gravity.

Lab-On-Chip Clinorotation System for Live-Cell Microscopy Under Simulated Microgravity

NASA Technical Reports Server (NTRS)

Yew, Alvin G.; Atencia, Javier; Chinn, Ben; Hsieh, Adam H.

1980-01-01

Cells in microgravity are subject to mechanical unloading and changes to the surrounding chemical environment. How these factors jointly influence cellular function is not well understood. We can investigate their role using ground-based analogues to spaceflight, where mechanical unloading is simulated through the time-averaged nullification of gravity. The prevailing method for cellular microgravity simulation is to use fluid-filled containers called clinostats. However, conventional clinostats are not designed for temporally tracking cell response, nor are they able to establish dynamic fluid environments. To address these needs, we developed a Clinorotation Time-lapse Microscopy (CTM) system that accommodates lab-on- chip cell culture devices for visualizing time-dependent alterations to cellular behavior. For the purpose of demonstrating CTM, we present preliminary results showing time-dependent differences in cell area between human mesenchymal stem cells (hMSCs) under modeled microgravity and normal gravity.

Attractor Structures of Signaling Networks: Consequences of Different Conformational Barcode Dynamics and Their Relations to Network-Based Drug Design.

PubMed

Szalay, Kristóf Z; Nussinov, Ruth; Csermely, Peter

2014-06-01

Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

Supporting High School Student Accomplishment of Biology Content Using Interactive Computer-Based Curricular Case Studies

NASA Astrophysics Data System (ADS)

Oliver, Joseph Steve; Hodges, Georgia W.; Moore, James N.; Cohen, Allan; Jang, Yoonsun; Brown, Scott A.; Kwon, Kyung A.; Jeong, Sophia; Raven, Sara P.; Jurkiewicz, Melissa; Robertson, Tom P.

2017-11-01

Research into the efficacy of modules featuring dynamic visualizations, case studies, and interactive learning environments is reported here. This quasi-experimental 2-year study examined the implementation of three interactive computer-based instructional modules within a curricular unit covering cellular biology concepts in an introductory high school biology course. The modules featured dynamic visualizations and focused on three processes that underlie much of cellular biology: diffusion, osmosis, and filtration. Pre-tests and post-tests were used to assess knowledge growth across the unit. A mixture Rasch model analysis of the post-test data revealed two groups of students. In both years of the study, a large proportion of the students were classified as low-achieving based on their pre-test scores. The use of the modules in the Cell Unit in year 2 was associated with a much larger proportion of the students having transitioned to the high-achieving group than in year 1. In year 2, the same teachers taught the same concepts as year 1 but incorporated the interactive computer-based modules into the cell biology unit of the curriculum. In year 2, 67% of students initially classified as low-achieving were classified as high-achieving at the end of the unit. Examination of responses to assessments embedded within the modules as well as post-test items linked transition to the high-achieving group with correct responses to items that both referenced the visualization and the contextualization of that visualization within the module. This study points to the importance of dynamic visualization within contextualized case studies as a means to support student knowledge acquisition in biology.

Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

PubMed

Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan

2018-05-30

Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.

Kinetic memory based on the enzyme-limited competition.

PubMed

Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

2014-08-01

Cellular memory, which allows cells to retain information from their environment, is important for a variety of cellular functions, such as adaptation to external stimuli, cell differentiation, and synaptic plasticity. Although posttranslational modifications have received much attention as a source of cellular memory, the mechanisms directing such alterations have not been fully uncovered. It may be possible to embed memory in multiple stable states in dynamical systems governing modifications. However, several experiments on modifications of proteins suggest long-term relaxation depending on experienced external conditions, without explicit switches over multi-stable states. As an alternative to a multistability memory scheme, we propose "kinetic memory" for epigenetic cellular memory, in which memory is stored as a slow-relaxation process far from a stable fixed state. Information from previous environmental exposure is retained as the long-term maintenance of a cellular state, rather than switches over fixed states. To demonstrate this kinetic memory, we study several models in which multimeric proteins undergo catalytic modifications (e.g., phosphorylation and methylation), and find that a slow relaxation process of the modification state, logarithmic in time, appears when the concentration of a catalyst (enzyme) involved in the modification reactions is lower than that of the substrates. Sharp transitions from a normal fast-relaxation phase into this slow-relaxation phase are revealed, and explained by enzyme-limited competition among modification reactions. The slow-relaxation process is confirmed by simulations of several models of catalytic reactions of protein modifications, and it enables the memorization of external stimuli, as its time course depends crucially on the history of the stimuli. This kinetic memory provides novel insight into a broad class of cellular memory and functions. In particular, applications for long-term potentiation are discussed, including dynamic modifications of calcium-calmodulin kinase II and cAMP-response element-binding protein essential for synaptic plasticity.

Cellular Particle Dynamics simulation of biomechanical relaxation processes of multi-cellular systems

NASA Astrophysics Data System (ADS)

McCune, Matthew; Kosztin, Ioan

2013-03-01

Cellular Particle Dynamics (CPD) is a theoretical-computational-experimental framework for describing and predicting the time evolution of biomechanical relaxation processes of multi-cellular systems, such as fusion, sorting and compression. In CPD, cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through numerical integration of their equations of motion. Here we present CPD simulation results for the fusion of both spherical and cylindrical multi-cellular aggregates. First, we calibrate the relevant CPD model parameters for a given cell type by comparing the CPD simulation results for the fusion of two spherical aggregates to the corresponding experimental results. Next, CPD simulations are used to predict the time evolution of the fusion of cylindrical aggregates. The latter is relevant for the formation of tubular multi-cellular structures (i.e., primitive blood vessels) created by the novel bioprinting technology. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Endele, Max; Etzrodt, Martin; Schroeder, Timm, E-mail: timm.schroeder@bsse.ethz.ch

Hematopoiesis is the cumulative consequence of finely tuned signaling pathways activated through extrinsic factors, such as local niche signals and systemic hematopoietic cytokines. Whether extrinsic factors actively instruct the lineage choice of hematopoietic stem and progenitor cells or are only selectively allowing survival and proliferation of already intrinsically lineage-committed cells has been debated over decades. Recent results demonstrated that cytokines can instruct lineage choice. However, the precise function of individual cytokine-triggered signaling molecules in inducing cellular events like proliferation, lineage choice, and differentiation remains largely elusive. Signal transduction pathways activated by different cytokine receptors are highly overlapping, but support themore » production of distinct hematopoietic lineages. Cellular context, signaling dynamics, and the crosstalk of different signaling pathways determine the cellular response of a given extrinsic signal. New tools to manipulate and continuously quantify signaling events at the single cell level are therefore required to thoroughly interrogate how dynamic signaling networks yield a specific cellular response. - Highlights: • Recent studies provided definite proof for lineage-instructive action of cytokines. • Signaling pathways involved in hematopoietic lineage instruction remain elusive. • New tools are emerging to quantitatively study dynamic signaling networks over time.« less

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear, transient dynamic finite element code, MSC.Dytran, was used to simulate an impact test of an energy absorbing Earth Entry Vehicle (EEV) that will impact without a parachute. EEVOs are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the center of the EEVOs cellular structure. Pre-test analytical predictions were compared with the test results from a bungee accelerator. The model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAM1 model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for cellular impact.

Analysis of Thermo-Diffusive Cellular Instabilities in Continuum Combustion Fronts

NASA Astrophysics Data System (ADS)

Azizi, Hossein; Gurevich, Sebastian; Provatas, Nikolas; Department of Physics, Centre Physics of Materials Team

We explore numerically the morphological patterns of thermo-diffusive instabilities in combustion fronts with a continuum solid fuel source, within a range of Lewis numbers, focusing on the cellular regime. Cellular and dendritic instabilities are found at low Lewis numbers. These are studied using a dynamic adaptive mesh refinement technique that allows very large computational domains, thus allowing us to reduce finite size effects that can affect or even preclude the emergence of these patterns. The distinct types of dynamics found in the vicinity of the critical Lewis number. These types of dynamics are classified as ``quasi-linear'' and characterized by low amplitude cells that may be strongly affected by the mode selection mechanism and growth prescribed by the linear theory. Below this range of Lewis number, highly non-linear effects become prominent and large amplitude, complex cellular and seaweed dendritic morphologies emerge. The cellular patterns simulated in this work are similar to those observed in experiments of flame propagation over a bed of nano-aluminum powder burning with a counter-flowing oxidizer conducted by Malchi et al. It is noteworthy that the physical dimension of our computational domain is roughly close to their experimental setup. This work was supported by a Canadian Space Agency Class Grant ''Percolating Reactive Waves in Particulate Suspensions''. We thank Compute Canada for computing resources.

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

PubMed

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

Multidimensional proteomics for cell biology.

PubMed

Larance, Mark; Lamond, Angus I

2015-05-01

The proteome is a dynamic system in which each protein has interconnected properties - dimensions - that together contribute to the phenotype of a cell. Measuring these properties has proved challenging owing to their diversity and dynamic nature. Advances in mass spectrometry-based proteomics now enable the measurement of multiple properties for thousands of proteins, including their abundance, isoform expression, turnover rate, subcellular localization, post-translational modifications and interactions. Complementing these experimental developments are new data analysis, integration and visualization tools as well as data-sharing resources. Together, these advances in the multidimensional analysis of the proteome are transforming our understanding of various cellular and physiological processes.

Allosteric dynamics of SAMHD1 studied by molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Patra, K. K.; Bhattacharya, A.; Bhattacharya, S.

2016-10-01

SAMHD1 is a human cellular enzyme that blocks HIV-1 infection in myeloid cells and non-cycling CD4+T cells. The enzyme is an allosterically regulated triphosphohydrolase that modulates the level of cellular dNTP. The virus restriction is attributed to the lowering of the pool of dNTP in the cell to a point where reverse-transcription is impaired. Mutations in SAMHD1 are also implicated in Aicardi-Goutieres syndrome. A mechanistic understanding of the allosteric activation of the enzyme is still elusive. We have performed molecular dynamics simulations to examine the allosteric site dynamics of the protein and to examine the connection between the stability of the tetrameric complex and the Allosite occupancy.

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

The endoplasmic reticulum: structure, function and response to cellular signaling.

PubMed

Schwarz, Dianne S; Blower, Michael D

2016-01-01

The endoplasmic reticulum (ER) is a large, dynamic structure that serves many roles in the cell including calcium storage, protein synthesis and lipid metabolism. The diverse functions of the ER are performed by distinct domains; consisting of tubules, sheets and the nuclear envelope. Several proteins that contribute to the overall architecture and dynamics of the ER have been identified, but many questions remain as to how the ER changes shape in response to cellular cues, cell type, cell cycle state and during development of the organism. Here we discuss what is known about the dynamics of the ER, what questions remain, and how coordinated responses add to the layers of regulation in this dynamic organelle.

Mechanism of Actin-Based Motility

NASA Astrophysics Data System (ADS)

Pantaloni, Dominique; Le Clainche, Christophe; Carlier, Marie-France

2001-05-01

Spatially controlled polymerization of actin is at the origin of cell motility and is responsible for the formation of cellular protrusions like lamellipodia. The pathogens Listeria monocytogenes and Shigella flexneri, which undergo actin-based propulsion, are acknowledged models of the leading edge of lamellipodia. Actin-based motility of the bacteria or of functionalized microspheres can be reconstituted in vitro from only five pure proteins. Movement results from the regulated site-directed treadmilling of actin filaments, consistent with observations of actin dynamics in living motile cells and with the biochemical properties of the components of the synthetic motility medium.

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY

PubMed Central

Somogyi, Endre; Hagar, Amit; Glazier, James A.

2017-01-01

Living tissues are dynamic, heterogeneous compositions of objects, including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes. Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology (CCOPM) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models. PMID:29282379

Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering

PubMed Central

Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P.; Tseng, Yiider

2010-01-01

Abstract The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes. PMID:20550894

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY.

PubMed

Somogyi, Endre; Hagar, Amit; Glazier, James A

2016-12-01

Living tissues are dynamic, heterogeneous compositions of objects , including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes . Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology ( CCOPM ) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Design of cryptographically secure AES like S-Box using second-order reversible cellular automata for wireless body area network applications.

PubMed

Gangadari, Bhoopal Rao; Rafi Ahamed, Shaik

2016-09-01

In biomedical, data security is the most expensive resource for wireless body area network applications. Cryptographic algorithms are used in order to protect the information against unauthorised access. Advanced encryption standard (AES) cryptographic algorithm plays a vital role in telemedicine applications. The authors propose a novel approach for design of substitution bytes (S-Box) using second-order reversible one-dimensional cellular automata (RCA 2 ) as a replacement to the classical look-up-table (LUT) based S-Box used in AES algorithm. The performance of proposed RCA 2 based S-Box and conventional LUT based S-Box is evaluated in terms of security using the cryptographic properties such as the nonlinearity, correlation immunity bias, strict avalanche criteria and entropy. Moreover, it is also shown that RCA 2 based S-Boxes are dynamic in nature, invertible and provide high level of security. Further, it is also found that the RCA 2 based S-Box have comparatively better performance than that of conventional LUT based S-Box.

Design of cryptographically secure AES like S-Box using second-order reversible cellular automata for wireless body area network applications

PubMed Central

Rafi Ahamed, Shaik

2016-01-01

In biomedical, data security is the most expensive resource for wireless body area network applications. Cryptographic algorithms are used in order to protect the information against unauthorised access. Advanced encryption standard (AES) cryptographic algorithm plays a vital role in telemedicine applications. The authors propose a novel approach for design of substitution bytes (S-Box) using second-order reversible one-dimensional cellular automata (RCA2) as a replacement to the classical look-up-table (LUT) based S-Box used in AES algorithm. The performance of proposed RCA2 based S-Box and conventional LUT based S-Box is evaluated in terms of security using the cryptographic properties such as the nonlinearity, correlation immunity bias, strict avalanche criteria and entropy. Moreover, it is also shown that RCA2 based S-Boxes are dynamic in nature, invertible and provide high level of security. Further, it is also found that the RCA2 based S-Box have comparatively better performance than that of conventional LUT based S-Box. PMID:27733924

Prognostic Value of Dynamic Monitoring of Cellular Immunity and HMGB1 in Severe Sepsis: Delayed Chronic Inflammation may be the Leading Cause of Death in Late Severe Sepsis.

PubMed

Yu, Han; Qi, Zhijiang; Zhao, Lianxing; Shao, Rui; Fang, Yingying; Li, Chunsheng

2016-12-01

Sepsis is a life-threatening response to infection with a high mortality rate. In order to explore the prognostic value of dynamic monitoring of cellular immunity during late severe sepsis, we assessed levels of Tlymphocyte subsets, the human leukocyte antigen D-related (HLA-DR), and the high mobility group box-1 (HMGB1) protein. Study participants included 247 consecutive severe sepsis patients who were admitted to Beijing ChaoYang Hospital's Emergency Intensive Care Unit. Patients were divided into survivors and non-survivors based on 90-day survival rates, and clinical data were collected. T-lymphocyte subsets on days 1 and 7, HLA-DR on days 1 and 12, and HMGB1 on days 1, 3, 5, 7, and 12 were analyzed. Counts of CD3+, CD3+CD4+, and CD3+CD8+ T cells on day 1 in non-survivors were lower than those in survivors. By day 7, counts of all three types of T cells had increased in both survivors and non-survivors, but CD3+ and CD3+CD8+ T cells remained lower in non-survivors than in survivors. There was no significant difference in HLA-DR levels between survivors and non-survivors on day 1, but HLA-DR levels increased in survivors and decreased in non-survivors by day 12. In contrast, over days 1 - 12, HMGB1 levels increased in non-survivors and decreased in survivors. Patients with severe sepsis present with cellular immune dysfunction and persistent chronic inflammation, both of which may lead to death in the late phase of severe sepsis. Dynamic monitoring of indicators of cellular immunity and HMGB1 is useful for evaluating the immune status, chronic inflammation processes, and prognoses of patients with severe sepsis.

Live imaging of dense-core vesicles in primary cultured hippocampal neurons.

PubMed

Kwinter, David M; Silverman, Michael A; Kwinter, David; Michael, Silverman

2009-05-29

Observing and characterizing dynamic cellular processes can yield important information about cellular activity that cannot be gained from static images. Vital fluorescent probes, particularly green fluorescent protein (GFP) have revolutionized cell biology stemming from the ability to label specific intracellular compartments and cellular structures. For example, the live imaging of GFP (and its spectral variants) chimeras have allowed for a dynamic analysis of the cytoskeleton, organelle transport, and membrane dynamics in a multitude of organisms and cell types [1-3]. Although live imaging has become prevalent, this approach still poses many technical challenges, particularly in primary cultured neurons. One challenge is the expression of GFP-tagged proteins in post-mitotic neurons; the other is the ability to capture fluorescent images while minimizing phototoxicity, photobleaching, and maintaining general cell health. Here we provide a protocol that describes a lipid-based transfection method that yields a relatively low transfection rate (~0.5%), however is ideal for the imaging of fully polarized neurons. A low transfection rate is essential so that single axons and dendrites can be characterized as to their orientation to the cell body to confirm directionality of transport, i.e., anterograde v. retrograde. Our approach to imaging GFP expressing neurons relies on a standard wide-field fluorescent microscope outfitted with a CCD camera, image capture software, and a heated imaging chamber. We have imaged a wide variety of organelles or structures, for example, dense-core vesicles, mitochondria, growth cones, and actin without any special optics or excitation requirements other than a fluorescent light source. Additionally, spectrally-distinct, fluorescently labeled proteins, e.g., GFP and dsRed-tagged proteins, can be visualized near simultaneously to characterize co-transport or other coordinated cellular events. The imaging approach described here is flexible for a variety of imaging applications and can be adopted by a laboratory for relatively little cost provided a microscope is available.

In vivo cell biology in zebrafish - providing insights into vertebrate development and disease.

PubMed

Vacaru, Ana M; Unlu, Gokhan; Spitzner, Marie; Mione, Marina; Knapik, Ela W; Sadler, Kirsten C

2014-02-01

Over the past decades, studies using zebrafish have significantly advanced our understanding of the cellular basis for development and human diseases. Zebrafish have rapidly developing transparent embryos that allow comprehensive imaging of embryogenesis combined with powerful genetic approaches. However, forward genetic screens in zebrafish have generated unanticipated findings that are mirrored by human genetic studies: disruption of genes implicated in basic cellular processes, such as protein secretion or cytoskeletal dynamics, causes discrete developmental or disease phenotypes. This is surprising because many processes that were assumed to be fundamental to the function and survival of all cell types appear instead to be regulated by cell-specific mechanisms. Such discoveries are facilitated by experiments in whole animals, where zebrafish provides an ideal model for visualization and manipulation of organelles and cellular processes in a live vertebrate. Here, we review well-characterized mutants and newly developed tools that underscore this notion. We focus on the secretory pathway and microtubule-based trafficking as illustrative examples of how studying cell biology in vivo using zebrafish has broadened our understanding of the role fundamental cellular processes play in embryogenesis and disease.

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry.

PubMed

Comi, Troy J; Do, Thanh D; Rubakhin, Stanislav S; Sweedler, Jonathan V

2017-03-22

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

Configurable Cellular Automata for Pseudorandom Number Generation

NASA Astrophysics Data System (ADS)

Quieta, Marie Therese; Guan, Sheng-Uei

This paper proposes a generalized structure of cellular automata (CA) — the configurable cellular automata (CoCA). With selected properties from programmable CA (PCA) and controllable CA (CCA), a new approach to cellular automata is developed. In CoCA, the cells are dynamically reconfigured at run-time via a control CA. Reconfiguration of a cell simply means varying the properties of that cell with time. Some examples of properties to be reconfigured are rule selection, boundary condition, and radius. While the objective of this paper is to propose CoCA as a new CA method, the main focus is to design a CoCA that can function as a good pseudorandom number generator (PRNG). As a PRNG, CoCA can be a suitable candidate as it can pass 17 out of 18 Diehard tests with 31 cells. CoCA PRNG's performance based on Diehard test is considered superior over other CA PRNG works. Moreover, CoCA opens new rooms for research not only in the field of random number generation, but in modeling complex systems as well.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.

PubMed

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-11-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.

Motifs, modules and games in bacteria.

PubMed

Wolf, Denise M; Arkin, Adam P

2003-04-01

Global explorations of regulatory network dynamics, organization and evolution have become tractable thanks to high-throughput sequencing and molecular measurement of bacterial physiology. From these, a nascent conceptual framework is developing, that views the principles of regulation in term of motifs, modules and games. Motifs are small, repeated, and conserved biological units ranging from molecular domains to small reaction networks. They are arranged into functional modules, genetically dissectible cellular functions such as the cell cycle, or different stress responses. The dynamical functioning of modules defines the organism's strategy to survive in a game, pitting cell against cell, and cell against environment. Placing pathway structure and dynamics into an evolutionary context begins to allow discrimination between those physical and molecular features that particularize a species to its surroundings, and those that provide core physiological function. This approach promises to generate a higher level understanding of cellular design, pathway evolution and cellular bioengineering.

Dynamic Reciprocity in the Wound Microenvironment

PubMed Central

Schultz, Gregory S.; Davidson, Jeffrey M.; Kirsner, Robert S.; Bornstein, Paul; Herman, Ira M.

2011-01-01

Here, we define dynamic reciprocity (DR) as an ongoing, bidirectional interaction amongst cells and their surrounding microenvironment. In the review, we posit that DR is especially meaningful during wound healing as the DR-driven biochemical, biophysical and cellular responses to injury play pivotal roles in regulating tissue regenerative responses. Such cell-extracellular matrix interactions not only guide and regulate cellular morphology, but cellular differentiation, migration, proliferation, and survival during tissue development, including e.g. embryogenesis, angiogenesis, as well as during pathologic processes including cancer diabetes, hypertension and chronic wound healing. Herein, we examine DR within the wound microenvironment while considering specific examples across acute and chronic wound healing. This review also considers how a number of hypotheses that attempt to explain chronic wound pathophysiology, which may be understood within the DR framework. The implications of applying the principles of dynamic reciprocity to optimize wound care practice and future development of innovative wound healing therapeutics are also briefly considered. PMID:21362080

Motifs, modules and games in bacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, Denise M.; Arkin, Adam P.

2003-04-01

Global explorations of regulatory network dynamics, organization and evolution have become tractable thanks to high-throughput sequencing and molecular measurement of bacterial physiology. From these, a nascent conceptual framework is developing, that views the principles of regulation in term of motifs, modules and games. Motifs are small, repeated, and conserved biological units ranging from molecular domains to small reaction networks. They are arranged into functional modules, genetically dissectible cellular functions such as the cell cycle, or different stress responses. The dynamical functioning of modules defines the organism's strategy to survive in a game, pitting cell against cell, and cell against environment.more » Placing pathway structure and dynamics into an evolutionary context begins to allow discrimination between those physical and molecular features that particularize a species to its surroundings, and those that provide core physiological function. This approach promises to generate a higher level understanding of cellular design, pathway evolution and cellular bioengineering.« less

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

In Vivo Biochemistry: Single-Cell Dynamics of Cyclic Di-GMP in Escherichia coli in Response to Zinc Overload.

PubMed

Yeo, Jongchan; Dippel, Andrew B; Wang, Xin C; Hammond, Ming C

2018-01-09

Intracellular signaling enzymes drive critical changes in cellular physiology and gene expression, but their endogenous activities in vivo remain highly challenging to study in real time and for individual cells. Here we show that flow cytometry can be performed in complex media to monitor single-cell population distributions and dynamics of cyclic di-GMP signaling, which controls the bacterial colonization program. These in vivo biochemistry experiments are enabled by our second-generation RNA-based fluorescent (RBF) biosensors, which exhibit high fluorescence turn-on in response to cyclic di-GMP. Specifically, we demonstrate that intracellular levels of cyclic di-GMP in Escherichia coli are repressed with excess zinc, but not with other divalent metals. Furthermore, in both flow cytometry and fluorescence microscopy setups, we monitor the dynamic increase in cellular cyclic di-GMP levels upon zinc depletion and show that this response is due to de-repression of the endogenous diguanylate cyclase DgcZ. In the presence of zinc, cells exhibit enhanced cell motility and increased sensitivity to antibiotics due to inhibited biofilm formation. Taken together, these results showcase the application of RBF biosensors in visualizing single-cell dynamic changes in cyclic di-GMP signaling in direct response to environmental cues such as zinc and highlight our ability to assess whether observed phenotypes are related to specific signaling enzymes and pathways.

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

Extinction rates in tumour public goods games.

PubMed

Gerlee, Philip; Altrock, Philipp M

2017-09-01

Cancer evolution and progression are shaped by cellular interactions and Darwinian selection. Evolutionary game theory incorporates both of these principles, and has been proposed as a framework to understand tumour cell population dynamics. A cornerstone of evolutionary dynamics is the replicator equation, which describes changes in the relative abundance of different cell types, and is able to predict evolutionary equilibria. Typically, the replicator equation focuses on differences in relative fitness. We here show that this framework might not be sufficient under all circumstances, as it neglects important aspects of population growth. Standard replicator dynamics might miss critical differences in the time it takes to reach an equilibrium, as this time also depends on cellular turnover in growing but bounded populations. As the system reaches a stable manifold, the time to reach equilibrium depends on cellular death and birth rates. These rates shape the time scales, in particular, in coevolutionary dynamics of growth factor producers and free-riders. Replicator dynamics might be an appropriate framework only when birth and death rates are of similar magnitude. Otherwise, population growth effects cannot be neglected when predicting the time to reach an equilibrium, and cell-type-specific rates have to be accounted for explicitly. © 2017 The Authors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

Elements of the cellular metabolic structure

PubMed Central

De la Fuente, Ildefonso M.

2015-01-01

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell. PMID:25988183

Using Long-Term Time-Lapse Imaging of Mammalian Cell Cycle Progression for Laboratory Instruction and Analysis

ERIC Educational Resources Information Center

Hinchcliffe, Edward H.

2005-01-01

Cinemicrography--the capture of moving cellular sequences through the microscope--has been influential in revealing the dynamic nature of cellular behavior. One of the more dramatic cellular events is mitosis, the division of sister chromatids into two daughter cells. Mitosis has been extensively studied in a variety of organisms, both…

Integrated electronics and fluidic MEMS for bioengineering

NASA Astrophysics Data System (ADS)

Fok, Ho Him Raymond

Microelectromechanical systems (MEMS) and microelectronics have become enabling technologies for many research areas. This dissertation presents the use of fluidic MEMS and microelectronics for bioengineering applications. In particular, the versatility of MEMS and microelectronics is highlighted by the presentation of two different applications, one for in-vitro study of nano-scale dynamics during cell division and one for in-vivo monitoring of biological activities at the cellular level. The first application of an integrated system discussed in this dissertation is to utilize fluidic MEMS for studying dynamics in the mitotic spindle, which could lead to better chemotherapeutic treatments for cancer patients. Previous work has developed the use of electrokinetic phenomena on the surface of a glass-based platform to assemble microtubules, the building blocks of mitotic spindles. Nevertheless, there are two important limitations of this type of platform. First, an unconventional microfabrication process is necessary for the glass-based platform, which limits the utility of this platform. In order to overcome this limitation, in this dissertation a convenient microfluidic system is fabricated using a negative photoresist called SU-8. The fabrication process for the SU-8-based system is compatible with other fabrication techniques used in developing microelectronics, and this compatibility is essential for integrating electronics for studying dynamics in the mitotic spindle. The second limitation of the previously-developed glass-based platform is its lack of bio-compatibility. For example, microtubules strongly interact with the surface of the glass-based platform, thereby hindering the study of dynamics in the mitotic spindle. This dissertation presents a novel approach for assembling microtubules away from the surface of the platform, and a fabrication process is developed to assemble microtubules between two self-aligned thin film electrodes on thick SU-8 pedestals. This approach also allows the in-vitro model to mimic the three-dimensionality of the cellular mitotic spindle that is absent in previous work. The second application of an integrated bioengineering system discussed in this dissertation is to design and fabricate active electronics and sensors for an in-vivo application to monitor neural activity at the cellular level. Temperature sensors were chosen for a first demonstration. In order for temperature sensors to be able to be implanted into brain interfaces, it is necessary for these devices to be fabricated using processes that are compatible with bio-compatible substrates such as glass and plastic. This dissertation addresses this challenge by developing temperature sensors integrated with biasing circuitry using zinc oxide thin film transistors (TFTs) fabricated on polyimide substrates. The integrated sensors show good temperature sensitivity, which is critical for monitoring neural temperature at the cellular level. This dissertation also describes the unique requirements of encapsulating implantable electronics. For instance, encapsulation schemes must be designed in such a way that they both protect electronic devices from extracellular fluids and also do not interfere with the functionality of these devices. In this work, SU-8 is used as a convenient and effective encapsulation layer. Thermal engineering to prevent active electronics from overheating and to ensure accurate temperature measurement from temperature sensors is also discussed, and a synergistic encapsulation and thermal engineering combination is presented.

Spin glass model for dynamics of cell reprogramming

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2015-03-01

Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor to another attractor. We perform Monte Carlo simulations in a simple model of the landscape. This model is based on spin glass theory and it can be used to construct a simulated epigenetic landscape starting from the experimental genomic data. We re-analyse data from several cell reprogramming experiments and compare with our simulation results. We find that the model can reproduce some of the main features of the dynamics of cell reprogramming.

Morphological communication: exploiting coupled dynamics in a complex mechanical structure to achieve locomotion

PubMed Central

Rieffel, John A.; Valero-Cuevas, Francisco J.; Lipson, Hod

2010-01-01

Traditional engineering approaches strive to avoid, or actively suppress, nonlinear dynamic coupling among components. Biological systems, in contrast, are often rife with these dynamics. Could there be, in some cases, a benefit to high degrees of dynamical coupling? Here we present a distributed robotic control scheme inspired by the biological phenomenon of tensegrity-based mechanotransduction. This emergence of morphology-as-information-conduit or ‘morphological communication’, enabled by time-sensitive spiking neural networks, presents a new paradigm for the decentralized control of large, coupled, modular systems. These results significantly bolster, both in magnitude and in form, the idea of morphological computation in robotic control. Furthermore, they lend further credence to ideas of embodied anatomical computation in biological systems, on scales ranging from cellular structures up to the tendinous networks of the human hand. PMID:19776146

Full-field dual-color 100-nm super-resolution imaging reveals organization and dynamics of mitochondrial and ER networks.

PubMed

Brunstein, Maia; Wicker, Kai; Hérault, Karine; Heintzmann, Rainer; Oheim, Martin

2013-11-04

Most structured illumination microscopes use a physical or synthetic grating that is projected into the sample plane to generate a periodic illumination pattern. Albeit simple and cost-effective, this arrangement hampers fast or multi-color acquisition, which is a critical requirement for time-lapse imaging of cellular and sub-cellular dynamics. In this study, we designed and implemented an interferometric approach allowing large-field, fast, dual-color imaging at an isotropic 100-nm resolution based on a sub-diffraction fringe pattern generated by the interference of two colliding evanescent waves. Our all-mirror-based system generates illumination pat-terns of arbitrary orientation and period, limited only by the illumination aperture (NA = 1.45), the response time of a fast, piezo-driven tip-tilt mirror (10 ms) and the available fluorescence signal. At low µW laser powers suitable for long-period observation of life cells and with a camera exposure time of 20 ms, our system permits the acquisition of super-resolved 50 µm by 50 µm images at 3.3 Hz. The possibility it offers for rapidly adjusting the pattern between images is particularly advantageous for experiments that require multi-scale and multi-color information. We demonstrate the performance of our instrument by imaging mitochondrial dynamics in cultured cortical astrocytes. As an illustration of dual-color excitation dual-color detection, we also resolve interaction sites between near-membrane mitochondria and the endoplasmic reticulum. Our TIRF-SIM microscope provides a versatile, compact and cost-effective arrangement for super-resolution imaging, allowing the investigation of co-localization and dynamic interactions between organelles--important questions in both cell biology and neurophysiology.

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

PubMed

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

Cell segmentation in time-lapse fluorescence microscopy with temporally varying sub-cellular fusion protein patterns.

PubMed

Bunyak, Filiz; Palaniappan, Kannappan; Chagin, Vadim; Cardoso, M

2009-01-01

Fluorescently tagged proteins such as GFP-PCNA produce rich dynamically varying textural patterns of foci distributed in the nucleus. This enables the behavioral study of sub-cellular structures during different phases of the cell cycle. The varying punctuate patterns of fluorescence, drastic changes in SNR, shape and position during mitosis and abundance of touching cells, however, require more sophisticated algorithms for reliable automatic cell segmentation and lineage analysis. Since the cell nuclei are non-uniform in appearance, a distribution-based modeling of foreground classes is essential. The recently proposed graph partitioning active contours (GPAC) algorithm supports region descriptors and flexible distance metrics. We extend GPAC for fluorescence-based cell segmentation using regional density functions and dramatically improve its efficiency for segmentation from O(N(4)) to O(N(2)), for an image with N(2) pixels, making it practical and scalable for high throughput microscopy imaging studies.

Traffic jam dynamics in stochastic cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagel, K.; Schreckenberg, M.

1995-09-01

Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA)more » and in NRW (Germany) for large scale microsimulations of network traffic.« less

Systems cell biology

PubMed Central

Mast, Fred D.; Ratushny, Alexander V.

2014-01-01

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. PMID:25225336

Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.

PubMed

Wikswo, J P; Prokop, A; Baudenbacher, F; Cliffel, D; Csukas, B; Velkovsky, M

2006-08-01

Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

Traffic dynamics of an on-ramp system with a cellular automaton model

NASA Astrophysics Data System (ADS)

Li, Xin-Gang; Gao, Zi-You; Jia, Bin; Jiang, Rui

2010-06-01

This paper uses the cellular automaton model to study the dynamics of traffic flow around an on-ramp with an acceleration lane. It adopts a parameter, which can reflect different lane-changing behaviour, to represent the diversity of driving behaviour. The refined cellular automaton model is used to describe the lower acceleration rate of a vehicle. The phase diagram and the capacity of the on-ramp system are investigated. The simulation results show that in the single cell model, the capacity of the on-ramp system will stay at the highest flow of a one lane system when the driver is moderate and careful; it will be reduced when the driver is aggressive. In the refined cellular automaton model, the capacity is always reduced even when the driver is careful. It proposes that the capacity drop of the on-ramp system is caused by aggressive lane-changing behaviour and lower acceleration rate.

Nanoparticles engineered to bind cellular motors for efficient delivery.

PubMed

Dalmau-Mena, Inmaculada; Del Pino, Pablo; Pelaz, Beatriz; Cuesta-Geijo, Miguel Ángel; Galindo, Inmaculada; Moros, María; de la Fuente, Jesús M; Alonso, Covadonga

2018-03-30

Dynein is a cytoskeletal molecular motor protein that transports cellular cargoes along microtubules. Biomimetic synthetic peptides designed to bind dynein have been shown to acquire dynamic properties such as cell accumulation and active intra- and inter-cellular motion through cell-to-cell contacts and projections to distant cells. On the basis of these properties dynein-binding peptides could be used to functionalize nanoparticles for drug delivery applications. Here, we show that gold nanoparticles modified with dynein-binding delivery sequences become mobile, powered by molecular motor proteins. Modified nanoparticles showed dynamic properties, such as travelling the cytosol, crossing intracellular barriers and shuttling the nuclear membrane. Furthermore, nanoparticles were transported from one cell to another through cell-to-cell contacts and quickly spread to distant cells through cell projections. The capacity of these motor-bound nanoparticles to spread to many cells and increasing cellular retention, thus avoiding losses and allowing lower dosage, could make them candidate carriers for drug delivery.

Selected contribution: a three-dimensional model for assessment of in vitro toxicity in balaena mysticetus renal tissue

NASA Technical Reports Server (NTRS)

Goodwin, T. J.; Coate-Li, L.; Linnehan, R. M.; Hammond, T. G.

2000-01-01

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.

[Homeostasis and Disorder of Musculoskeletal System.Cellular dynamics in musculoskeletal system visualized by intravital imaging techniques.

PubMed

Kikuta, Junichi; Ishii, Masaru

Bone is continually remodeled by bone-resorbing osteoclasts and bone-forming osteoblasts. Although it has long been believed that bone homeostasis is tightly regulated by communication between osteoclasts and osteoblasts, the fundamental process and dynamics have remained elusive. We originally established an advanced imaging system to visualize living bone tissues using intravital two-photon microscopy. By means of this system, we revealed the in vivo behavior of bone-resorbing osteoclasts and bone-forming osteoblasts in bone tissues. This approach facilitates investigation of cellular dynamics in the pathogenesis of musculoskeletal disorders, and would thus be useful for evaluating the efficacy of novel therapeutic agents.

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Temporal and mechanistic tracking of cellular uptake dynamics with novel surface fluorophore-bound nanodiamonds.

PubMed

Schrand, Amanda M; Lin, Jonathan B; Hens, Suzanne Ciftan; Hussain, Saber M

2011-02-01

Nanoparticles (NPs) offer promise for a multitude of biological applications including cellular probes at the bio-interface for targeted delivery of anticancer substances, Raman and fluorescent-based imaging and directed cell growth. Nanodiamonds (NDs), in particular, have several advantages compared to other carbon-based nanomaterials - including a rich surface chemistry useful for chemical conjugation, high biocompatibility with little reactive oxygen species (ROS) generation, physical and chemical stability that affords sterilization, high surface area to volume ratio, transparency and a high index of refraction. The visualization of ND internalization into cells is possible via photoluminescence, which is produced by direct dye conjugation or high energy irradiation that creates nitrogen vacancy centers. Here, we explore the kinetics and mechanisms involved in the intracellular uptake and localization of novel, highly-stable, fluorophore-conjugated NDs. Examination in a neuronal cell line (N2A) shows ND localization to early endosomes and lysosomes with eventual release into the cytoplasm. The addition of endocytosis and exocytosis inhibitors allows for diminished uptake and increased accumulation, respectively, which further corroborates cellular behavior in response to NDs. Ultimately, the ability of the NDs to travel throughout cellular compartments of varying pH without degradation of the surface-conjugated fluorophore or alteration of cell viability over extended periods of time is promising for their use in biomedical applications as stable, biocompatible, fluorescent probes.

Fasting and refeeding induces changes in the mouse hepatic lipid droplet proteome.

PubMed

Kramer, David A; Quiroga, Ariel D; Lian, Jihong; Fahlman, Richard P; Lehner, Richard

2018-06-15

During fasting, the liver increases lipid storage as a mean to reserve and provide energy for vital cellular functions. After re-feeding, hepatocytes rapidly decrease the amount of triacylglycerol that is stored in lipid droplets (LDs), visible as the size of hepatic LDs significantly decreases after re-feeding. Little is known about the changes in the liver LD proteome that occur during the fasting/re-feeding transition. This study aimed to investigate the hepatic LD proteome in fasted and re-fed conditions in the mouse. Using label-free LC-MS/MS analysis the relative abundance of 817 proteins was determined in highly purified LDs. Comparative analysis for differential protein abundance with respect to feeding states revealed 130 with higher abundance in LDs from fasted mice and 31 in LDs from re-fed mice. Among proteins observed to have higher abundance on LDs in the fasted state we found perilipin-5, and several mitochondrial and peroxisomal marker proteins, supporting the role of LDs in the provision of substrates for fatty acid oxidation. Proteins of higher abundance upon re-feeding included several peroxisomal and mitochondrial marker proteins and expand our understanding of the dynamic nature of the hepatic LD proteome according to the energetic requirements of the cell. Proteomic investigations have been revealing the complexities and dynamics of cellular LDs from a variety of cell types. As these sub-cellular structures are truly dynamic in nature, our investigations reveal that simply the feeding state of an animal leads to significant changes to the protein composition of LDs and suggest a variety of dynamic interactions with other cellular organelles, such as the mitochondria and peroxisomes. As such, the experimental design for investigations of this cellular structure must consider this dynamic baseline. Lastly our analysis on global protein abundance has revealed the unforeseen high abundance of murine major urinary proteins associated with hepatic lipid droplets, which warrants further investigations. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Electoral surveys’ influence on the voting processes: a cellular automata model

NASA Astrophysics Data System (ADS)

Alves, S. G.; Oliveira Neto, N. M.; Martins, M. L.

2002-12-01

Nowadays, in societies threatened by atomization, selfishness, short-term thinking, and alienation from political life, there is a renewed debate about classical questions concerning the quality of democratic decision making. In this work a cellular automata model for the dynamics of free elections, based on the social impact theory is proposed. By using computer simulations, power-law distributions for the size of electoral clusters and decision time have been obtained. The major role of broadcasted electoral surveys in guiding opinion formation and stabilizing the “status quo” was demonstrated. Furthermore, it was shown that in societies where these surveys are manipulated within the universally accepted statistical error bars, even a majoritary opposition could be hindered from reaching power through the electoral path.

UnPAKing the class differences among p21-activated kinases.

PubMed

Eswaran, Jeyanthy; Soundararajan, Meera; Kumar, Rakesh; Knapp, Stefan

2008-08-01

The p21-activated kinases (PAKs) are signal transducers, central to many vital cellular processes, including cell morphology, motility, survival, gene transcription and hormone signalling. The mammalian PAK family contains six serine/threonine kinases divided into two subgroups, group I (PAK 1-3) and group II (PAK4-6), based on their domain architecture and regulation. PAKs functioning as dynamic signalling nodes present themselves as attractive therapeutic targets in tumours, neurological diseases and infection. The recent findings across all PAKs, including newly reported structures, shed light on the cellular functions of PAKs, highlighting molecular mechanisms of activation, catalysis and substrate specificity. We believe that a comprehensive understanding of the entire PAK family is essential for developing strategies towards PAK-targeted therapeutics.

In vitro studies of actin filament and network dynamics

PubMed Central

Mullins, R Dyche; Hansen, Scott D

2013-01-01

Now that many genomes have been sequenced, a central concern of cell biology is to understand how the proteins they encode work together to create living matter. In vitro studies form an essential part of this program because understanding cellular functions of biological molecules often requires isolating them and reconstituting their activities. In particular, many elements of the actin cytoskeleton were first discovered by biochemical methods and their cellular functions deduced from in vitro experiments. We highlight recent advances that have come from in vitro studies, beginning with studies of actin filaments, and ending with multi-component reconstitutions of complex actin-based processes, including force-generation and cell spreading. We describe both scientific results and the technical innovations that made them possible. PMID:23267766

Natural photoreceptors and their application to synthetic biology.

PubMed

Schmidt, Daniel; Cho, Yong Ku

2015-02-01

The ability to perturb living systems is essential to understand how cells sense, integrate, and exchange information, to comprehend how pathologic changes in these processes relate to disease, and to provide insights into therapeutic points of intervention. Several molecular technologies based on natural photoreceptor systems have been pioneered that allow distinct cellular signaling pathways to be modulated with light in a temporally and spatially precise manner. In this review, we describe and discuss the underlying design principles of natural photoreceptors that have emerged as fundamental for the rational design and implementation of synthetic light-controlled signaling systems. Furthermore, we examine the unique challenges that synthetic protein technologies face when applied to the study of neural dynamics at the cellular and network level. Published by Elsevier Ltd.

Non-invasive breast biopsy method using GD-DTPA contrast enhanced MRI series and F-18-FDG PET/CT dynamic image series

NASA Astrophysics Data System (ADS)

Magri, Alphonso William

This study was undertaken to develop a nonsurgical breast biopsy from Gd-DTPA Contrast Enhanced Magnetic Resonance (CE-MR) images and F-18-FDG PET/CT dynamic image series. A five-step process was developed to accomplish this. (1) Dynamic PET series were nonrigidly registered to the initial frame using a finite element method (FEM) based registration that requires fiducial skin markers to sample the displacement field between image frames. A commercial FEM package (ANSYS) was used for meshing and FEM calculations. Dynamic PET image series registrations were evaluated using similarity measurements SAVD and NCC. (2) Dynamic CE-MR series were nonrigidly registered to the initial frame using two registration methods: a multi-resolution free-form deformation (FFD) registration driven by normalized mutual information, and a FEM-based registration method. Dynamic CE-MR image series registrations were evaluated using similarity measurements, localization measurements, and qualitative comparison of motion artifacts. FFD registration was found to be superior to FEM-based registration. (3) Nonlinear curve fitting was performed for each voxel of the PET/CT volume of activity versus time, based on a realistic two-compartmental Patlak model. Three parameters for this model were fitted; two of them describe the activity levels in the blood and in the cellular compartment, while the third characterizes the washout rate of F-18-FDG from the cellular compartment. (4) Nonlinear curve fitting was performed for each voxel of the MR volume of signal intensity versus time, based on a realistic two-compartment Brix model. Three parameters for this model were fitted: rate of Gd exiting the compartment, representing the extracellular space of a lesion; rate of Gd exiting a blood compartment; and a parameter that characterizes the strength of signal intensities. Curve fitting used for PET/CT and MR series was accomplished by application of the Levenburg-Marquardt nonlinear regression algorithm. The best-fit parameters were used to create 3D parametric images. Compartmental modeling evaluation was based on the ability of parameter values to differentiate between tissue types. This evaluation was used on registered and unregistered image series and found that registration improved results. (5) PET and MR parametric images were registered through FEM- and FFD-based registration. Parametric image registration was evaluated using similarity measurements, target registration error, and qualitative comparison. Comparing FFD and FEM-based registration results showed that the FEM method is superior. This five-step process constitutes a novel multifaceted approach to a nonsurgical breast biopsy that successfully executes each step. Comparison of this method to biopsy still needs to be done with a larger set of subject data.

Nonlinear dynamics of C–terminal tails in cellular microtubules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sekulic, Dalibor L., E-mail: dalsek@uns.ac.rs; Sataric, Bogdan M.; Sataric, Miljko V.

2016-07-15

The mechanical and electrical properties, and information processing capabilities of microtubules are the permanent subject of interest for carrying out experiments in vitro and in silico, as well as for theoretical attempts to elucidate the underlying processes. In this paper, we developed a new model of the mechano–electrical waves elicited in the rows of very flexible C–terminal tails which decorate the outer surface of each microtubule. The fact that C–terminal tails play very diverse roles in many cellular functions, such as recruitment of motor proteins and microtubule–associated proteins, motivated us to consider their collective dynamics as the source of localizedmore » waves aimed for communication between microtubule and associated proteins. Our approach is based on the ferroelectric liquid crystal model and it leads to the effective asymmetric double-well potential which brings about the conditions for the appearance of kink–waves conducted by intrinsic electric fields embedded in microtubules. These kinks can serve as the signals for control and regulation of intracellular traffic along microtubules performed by processive motions of motor proteins, primarly from kinesin and dynein families. On the other hand, they can be precursors for initiation of dynamical instability of microtubules by recruiting the proper proteins responsible for the depolymerization process.« less

Reversible and Dynamic Fluorescence Imaging of Cellular Redox Self-Regulation Using Fast-Responsive Near-Infrared Ge-Pyronines.

PubMed

Nie, Hailiang; Jing, Jing; Tian, Yong; Yang, Wen; Zhang, Rubo; Zhang, Xiaoling

2016-04-13

Cellular self-regulation of reactive oxygen species (ROS) stress via glutathione (GSH) antioxidant repair plays a crucial role in maintaining redox balance, which affects various physiological and pathological pathways. In this work, we developed a simple yet effective strategy for reversible, dynamic, and real-time fluorescence imaging of ROS stress and GSH repair, based on novel Ge-pyronine dyes (GePs). Unlike the current O-pyronine (OP) dye, the fluorescence of GePs can be quenched in GSH reduction and then greatly restored by ROS (e.g., ClO(-), ONOO(-), and HO(•)) oxidation because of their unique affinity toward thiols. The "on-off" and "off-on" fluorescence switch can complete in 10 and 20 s, respectively, and exhibit excellent reversibility in vitro and in cells. GePs also show excitation in the long wavelength from the deep-red to near-infrared (NIR) (621-662 nm) region, high fluorescence quantum yield (Φ(fl) = 0.32-0.44) in aqueous media, and excellent cell permeability. Our results demonstrated that GePs can be used for real-time monitoring of the reversible and dynamic interconversion between ROS oxidation and GSH reduction in living cells. GePs might be a useful tool for investigating various redox-related physiological and pathological pathways.

VISUALIZIATION OF CELLULAR PHOSPHOINOSITIDE POOLS WITH GFP-FUSED PROTEIN-DOMAINS

PubMed Central

Balla, Tamas; Várnai, Péter

2011-01-01

This unit describes the method of following phosphoinositide dynamics in live cells. Inositol phospholipids have emerged as universal signaling molecules present in virtually every membrane of eukaryotic cells. Phosphoinositides are present only in tiny amounts compared to structural lipids but are metabolically very active as they are produced and degraded by the numerous inositide kinase and phosphatase enzymes. Phosphoinositides control the membrane-recruitment and activity of many protein signaling-complexes in specific membrane compartments and have been implicated in the regulation of a variety of signaling and trafficking pathways. It has been a challenge to develop methods that allow detection of phosphoinositides at the single cell level. The only available technique in live cell application is based on the use of the same protein domains selected by evolution to recognize cellular phosphoinositides. Some of these isolated protein modules when fused to fluorescent proteins can follow dynamic changes in phosphoinositides. While this technique can provide information on phosphoinositide dynamics in live cells with subcellular resolution and rapidly gained popularity, it also has several limitations that must be taken into account when interpreting the data. Here, we summarize the design and practical use of these constructs and also review important considerations for the interpretation of the data obtained by this technique. PMID:19283730

Time-lapse electrical impedance spectroscopy for monitoring the cell cycle of single immobilized S. pombe cells.

PubMed

Zhu, Zhen; Frey, Olivier; Haandbaek, Niels; Franke, Felix; Rudolf, Fabian; Hierlemann, Andreas

2015-11-26

As a complement and alternative to optical methods, wide-band electrical impedance spectroscopy (EIS) enables multi-parameter, label-free and real-time detection of cellular and subcellular features. We report on a microfluidics-based system designed to reliably capture single rod-shaped Schizosaccharomyces pombe cells by applying suction through orifices in a channel wall. The system enables subsequent culturing of immobilized cells in an upright position, while dynamic changes in cell-cycle state and morphology were continuously monitored through EIS over a broad frequency range. Besides measuring cell growth, clear impedance signals for nuclear division have been obtained. The EIS system has been characterized with respect to sensitivity and detection limits. The spatial resolution in measuring cell length was 0.25 μm, which corresponds to approximately a 5-min interval of cell growth under standard conditions. The comprehensive impedance data sets were also used to determine the occurrence of nuclear division and cytokinesis. The obtained results have been validated through concurrent confocal imaging and plausibilized through comparison with finite-element modeling data. The possibility to monitor cellular and intracellular features of single S. pombe cells during the cell cycle at high spatiotemporal resolution renders the presented microfluidics-based EIS system a suitable tool for dynamic single-cell investigations.

Time-lapse electrical impedance spectroscopy for monitoring the cell cycle of single immobilized S. pombe cells

PubMed Central

Zhu, Zhen; Frey, Olivier; Haandbaek, Niels; Franke, Felix; Rudolf, Fabian; Hierlemann, Andreas

2015-01-01

As a complement and alternative to optical methods, wide-band electrical impedance spectroscopy (EIS) enables multi-parameter, label-free and real-time detection of cellular and subcellular features. We report on a microfluidics-based system designed to reliably capture single rod-shaped Schizosaccharomyces pombe cells by applying suction through orifices in a channel wall. The system enables subsequent culturing of immobilized cells in an upright position, while dynamic changes in cell-cycle state and morphology were continuously monitored through EIS over a broad frequency range. Besides measuring cell growth, clear impedance signals for nuclear division have been obtained. The EIS system has been characterized with respect to sensitivity and detection limits. The spatial resolution in measuring cell length was 0.25 μm, which corresponds to approximately a 5-min interval of cell growth under standard conditions. The comprehensive impedance data sets were also used to determine the occurrence of nuclear division and cytokinesis. The obtained results have been validated through concurrent confocal imaging and plausibilized through comparison with finite-element modeling data. The possibility to monitor cellular and intracellular features of single S. pombe cells during the cell cycle at high spatiotemporal resolution renders the presented microfluidics-based EIS system a suitable tool for dynamic single-cell investigations. PMID:26608589

Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

PubMed Central

Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

2010-01-01

Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

Clinically translatable nanotheranostic platforms for peripheral nerve regeneration: design with outcome in mind

NASA Astrophysics Data System (ADS)

Janjic, Jelena M.; Gorantla, Vijay S.

2018-02-01

Neuroinflammation is a dynamic immune phenomenon that changes in severity with time after neurotrauma and has a profound impact on neuroregeneration, tissue healing and neuropathic pain, which is a common consequence of peripheral nerve injury (PNI). Macrophages are key cellular mediators of neuroinflammation. Macrophage-targeted nanotherapies, such as complex (perfluorocarbon/hydrocarbon) multimodal nanoemulsions (NEs) provide highly specific imaging signatures of neuroinflammation and hence indirect surrogate metrics of regeneration. We present a novel strategy where these NEs incorporating multiple imaging modalities and biosensors are delivered locally to directly target key cellular players of neuroregeneration. Two representative formulations of a nanotheranostic platform for local delivery of cell targeted NEs are presented: 1) A dual (macrophage and neuronal) targeted nanoparticle laden hydrogel for synergistic modulation of neuroinflammation and analgesia following PNI; and 2) neurotherapeutic loaded nanoparticles with extended release profile for sustained support of neuroregeneration. Each platform is capable of dual imaging payloads (NIRF, MRI and/or PET) and/or cell specific targeting moieties for controlled drug release. In vitro and pilot in vivo results will be presented. Theranostic nanosystem based platforms offer a unique opportunity to sequentially monitor cellular and molecular events at the site of neuronal injury, enabling dynamic, in-vivo mechanistic insights rather than static, ex-vivo histopathologic evaluation. Given their targeted capabilities, these platforms can help achieve personalized treatments that are customized and optimized for patients with PNI.

Differential effects of LifeAct-GFP and actin-GFP on cell mechanics assessed using micropipette aspiration.

PubMed

Sliogeryte, Kristina; Thorpe, Stephen D; Wang, Zhao; Thompson, Clare L; Gavara, Nuria; Knight, Martin M

2016-01-25

The actin cytoskeleton forms a dynamic structure involved in many fundamental cellular processes including the control of cell morphology, migration and biomechanics. Recently LifeAct-GFP (green fluorescent protein) has been proposed for visualising actin structure and dynamics in live cells as an alternative to actin-GFP which has been shown to affect cell mechanics. Here we compare the two approaches in terms of their effect on cellular mechanical behaviour. Human mesenchymal stem cells (hMSCs) were analysed using micropipette aspiration and the effective cellular equilibrium and instantaneous moduli calculated using the standard linear solid model. We show that LifeAct-GFP provides clearer visualisation of F-actin organisation and dynamics. Furthermore, LifeAct-GFP does not alter effective cellular mechanical properties whereas actin-GFP expression causes an increase in the cell modulus. Interestingly, LifeAct-GFP expression did produce a small (~10%) increase in the percentage of cells exhibiting aspiration-induced membrane bleb formation, whilst actin-GFP expression reduced blebbing. Further studies examined the influence of LifeAct-GFP in other cell types, namely chondrogenically differentiated hMSCs and murine chondrocytes. LifeAct-GFP also had no effect on the moduli of these non-blebbing cells for which mechanical properties are largely dependent on the actin cortex. In conclusion we show that LifeAct-GFP enables clearer visualisation of actin organisation and dynamics without disruption of the biomechanical properties of either the whole cell or the actin cortex. Thus the study provides new evidence supporting the use of LifeAct-GFP rather than actin-GFP for live cell microscopy and the study of cellular mechanobiology. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Impact of release dynamics of laser-irradiated polymer micropallets on the viability of selected adherent cells

PubMed Central

Ma, Huan; Mismar, Wael; Wang, Yuli; Small, Donald W.; Ras, Mat; Allbritton, Nancy L.; Sims, Christopher E.; Venugopalan, Vasan

2012-01-01

We use time-resolved interferometry, fluorescence assays and computational fluid dynamics (CFD) simulations to examine the viability of confluent adherent cell monolayers to selection via laser microbeam release of photoresist polymer micropallets. We demonstrate the importance of laser microbeam pulse energy and focal volume position relative to the glass–pallet interface in governing the threshold energies for pallet release as well as the pallet release dynamics. Measurements using time-resolved interferometry show that increases in laser pulse energy result in increasing pallet release velocities that can approach 10 m s−1 through aqueous media. CFD simulations reveal that the pallet motion results in cellular exposure to transient hydrodynamic shear stress amplitudes that can exceed 100 kPa on microsecond timescales, and which produces reduced cell viability. Moreover, CFD simulation results show that the maximum shear stress on the pallet surface varies spatially, with the largest shear stresses occurring on the pallet periphery. Cell viability of confluent cell monolayers on the pallet surface confirms that the use of larger pulse energies results in increased rates of necrosis for those cells situated away from the pallet centre, while cells situated at the pallet centre remain viable. Nevertheless, experiments that examine the viability of these cell monolayers following pallet release show that proper choices for laser microbeam pulse energy and focal volume position lead to the routine achievement of cell viability in excess of 90 per cent. These laser microbeam parameters result in maximum pallet release velocities below 6 m s−1 and cellular exposure of transient hydrodynamic shear stresses below 20 kPa. Collectively, these results provide a mechanistic understanding that relates pallet release dynamics and associated transient shear stresses with subsequent cellular viability. This provides a quantitative, mechanistic basis for determining optimal operating conditions for laser microbeam-based pallet release systems for the isolation and selection of adherent cells. PMID:22158840

Impact of release dynamics of laser-irradiated polymer micropallets on the viability of selected adherent cells.

PubMed

Ma, Huan; Mismar, Wael; Wang, Yuli; Small, Donald W; Ras, Mat; Allbritton, Nancy L; Sims, Christopher E; Venugopalan, Vasan

2012-06-07

We use time-resolved interferometry, fluorescence assays and computational fluid dynamics (CFD) simulations to examine the viability of confluent adherent cell monolayers to selection via laser microbeam release of photoresist polymer micropallets. We demonstrate the importance of laser microbeam pulse energy and focal volume position relative to the glass-pallet interface in governing the threshold energies for pallet release as well as the pallet release dynamics. Measurements using time-resolved interferometry show that increases in laser pulse energy result in increasing pallet release velocities that can approach 10 m s(-1) through aqueous media. CFD simulations reveal that the pallet motion results in cellular exposure to transient hydrodynamic shear stress amplitudes that can exceed 100 kPa on microsecond timescales, and which produces reduced cell viability. Moreover, CFD simulation results show that the maximum shear stress on the pallet surface varies spatially, with the largest shear stresses occurring on the pallet periphery. Cell viability of confluent cell monolayers on the pallet surface confirms that the use of larger pulse energies results in increased rates of necrosis for those cells situated away from the pallet centre, while cells situated at the pallet centre remain viable. Nevertheless, experiments that examine the viability of these cell monolayers following pallet release show that proper choices for laser microbeam pulse energy and focal volume position lead to the routine achievement of cell viability in excess of 90 per cent. These laser microbeam parameters result in maximum pallet release velocities below 6 m s(-1) and cellular exposure of transient hydrodynamic shear stresses below 20 kPa. Collectively, these results provide a mechanistic understanding that relates pallet release dynamics and associated transient shear stresses with subsequent cellular viability. This provides a quantitative, mechanistic basis for determining optimal operating conditions for laser microbeam-based pallet release systems for the isolation and selection of adherent cells.

Systems cell biology.

PubMed

Mast, Fred D; Ratushny, Alexander V; Aitchison, John D

2014-09-15

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. © 2014 Mast et al.

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

Convergence dynamics and pseudo almost periodicity of a class of nonautonomous RFDEs with applications

NASA Astrophysics Data System (ADS)

Fan, Meng; Ye, Dan

2005-09-01

This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.

Nonlinear dynamics of the cellular-automaton ``game of Life''

NASA Astrophysics Data System (ADS)

Garcia, J. B. C.; Gomes, M. A. F.; Jyh, T. I.; Ren, T. I.; Sales, T. R. M.

1993-11-01

A statistical analysis of the ``game of Life'' due to Conway [Berlekamp, Conway, and Guy, Winning Ways for Your Mathematical Plays (Academic, New York, 1982), Vol. 2] is reported. The results are based on extensive computer simulations starting with uncorrelated distributions of live sites at t=0. The number n(s,t) of clusters of s live sites at time t, the mean cluster size s¯(t), and the diversity of sizes among other statistical functions are obtained. The dependence of the statistical functions with the initial density of live sites is examined. Several scaling relations as well as static and dynamic critical exponents are found.

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity

PubMed Central

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand “complex behavior” and complexity theory, and from which important biological insight can be gained. PMID:24999297

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity.

PubMed

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand "complex behavior" and complexity theory, and from which important biological insight can be gained.

Dynamic imaging of adaptive stress response pathway activation for prediction of drug induced liver injury.

PubMed

Wink, Steven; Hiemstra, Steven W; Huppelschoten, Suzanne; Klip, Janna E; van de Water, Bob

2018-05-01

Drug-induced liver injury remains a concern during drug treatment and development. There is an urgent need for improved mechanistic understanding and prediction of DILI liabilities using in vitro approaches. We have established and characterized a panel of liver cell models containing mechanism-based fluorescent protein toxicity pathway reporters to quantitatively assess the dynamics of cellular stress response pathway activation at the single cell level using automated live cell imaging. We have systematically evaluated the application of four key adaptive stress pathway reporters for the prediction of DILI liability: SRXN1-GFP (oxidative stress), CHOP-GFP (ER stress/UPR response), p21 (p53-mediated DNA damage-related response) and ICAM1 (NF-κB-mediated inflammatory signaling). 118 FDA-labeled drugs in five human exposure relevant concentrations were evaluated for reporter activation using live cell confocal imaging. Quantitative data analysis revealed activation of single or multiple reporters by most drugs in a concentration and time dependent manner. Hierarchical clustering of time course dynamics and refined single cell analysis allowed the allusion of key events in DILI liability. Concentration response modeling was performed to calculate benchmark concentrations (BMCs). Extracted temporal dynamic parameters and BMCs were used to assess the predictive power of sub-lethal adaptive stress pathway activation. Although cellular adaptive responses were activated by non-DILI and severe-DILI compounds alike, dynamic behavior and lower BMCs of pathway activation were sufficiently distinct between these compound classes. The high-level detailed temporal- and concentration-dependent evaluation of the dynamics of adaptive stress pathway activation adds to the overall understanding and prediction of drug-induced liver liabilities.

Live CLEM imaging to analyze nuclear structures at high resolution.

PubMed

Haraguchi, Tokuko; Osakada, Hiroko; Koujin, Takako

2015-01-01

Fluorescence microscopy (FM) and electron microscopy (EM) are powerful tools for observing molecular components in cells. FM can provide temporal information about cellular proteins and structures in living cells. EM provides nanometer resolution images of cellular structures in fixed cells. We have combined FM and EM to develop a new method of correlative light and electron microscopy (CLEM), called "Live CLEM." In this method, the dynamic behavior of specific molecules of interest is first observed in living cells using fluorescence microscopy (FM) and then cellular structures in the same cell are observed using electron microscopy (EM). Following image acquisition, FM and EM images are compared to enable the fluorescent images to be correlated with the high-resolution images of cellular structures obtained using EM. As this method enables analysis of dynamic events involving specific molecules of interest in the context of specific cellular structures at high resolution, it is useful for the study of nuclear structures including nuclear bodies. Here we describe Live CLEM that can be applied to the study of nuclear structures in mammalian cells.

Quantitative analysis of tissue deformation dynamics reveals three characteristic growth modes and globally aligned anisotropic tissue deformation during chick limb development.

PubMed

Morishita, Yoshihiro; Kuroiwa, Atsushi; Suzuki, Takayuki

2015-05-01

Tissue-level characterization of deformation dynamics is crucial for understanding organ morphogenetic mechanisms, especially the interhierarchical links among molecular activities, cellular behaviors and tissue/organ morphogenetic processes. Limb development is a well-studied topic in vertebrate organogenesis. Nevertheless, there is still little understanding of tissue-level deformation relative to molecular and cellular dynamics. This is mainly because live recording of detailed cell behaviors in whole tissues is technically difficult. To overcome this limitation, by applying a recently developed Bayesian approach, we here constructed tissue deformation maps for chick limb development with high precision, based on snapshot lineage tracing using dye injection. The precision of the constructed maps was validated with a clear statistical criterion. From the geometrical analysis of the map, we identified three characteristic tissue growth modes in the limb and showed that they are consistent with local growth factor activity and cell cycle length. In particular, we report that SHH signaling activity changes dynamically with developmental stage and strongly correlates with the dynamic shift in the tissue growth mode. We also found anisotropic tissue deformation along the proximal-distal axis. Morphogenetic simulation and experimental studies suggested that this directional tissue elongation, and not local growth, has the greatest impact on limb shaping. This result was supported by the novel finding that anisotropic tissue elongation along the proximal-distal axis occurs independently of cell proliferation. Our study marks a pivotal point for multi-scale system understanding in vertebrate development. © 2015. Published by The Company of Biologists Ltd.

Density-based clustering analyses to identify heterogeneous cellular sub-populations

NASA Astrophysics Data System (ADS)

Heaster, Tiffany M.; Walsh, Alex J.; Landman, Bennett A.; Skala, Melissa C.

2017-02-01

Autofluorescence microscopy of NAD(P)H and FAD provides functional metabolic measurements at the single-cell level. Here, density-based clustering algorithms were applied to metabolic autofluorescence measurements to identify cell-level heterogeneity in tumor cell cultures. The performance of the density-based clustering algorithm, DENCLUE, was tested in samples with known heterogeneity (co-cultures of breast carcinoma lines). DENCLUE was found to better represent the distribution of cell clusters compared to Gaussian mixture modeling. Overall, DENCLUE is a promising approach to quantify cell-level heterogeneity, and could be used to understand single cell population dynamics in cancer progression and treatment.

Microfluidic platform for single cell analysis under dynamic spatial and temporal stimulation.

PubMed

Song, Jiyoung; Ryu, Hyunryul; Chung, Minhwan; Kim, Youngtaek; Blum, Yannick; Lee, Sung Sik; Pertz, Olivier; Jeon, Noo Li

2018-05-01

Recent research on cellular responses is shifting from static observations recorded under static stimuli to real-time monitoring in a dynamic environment. Since cells sense and interact with their surrounding microenvironment, an experimental platform where dynamically changing cellular microenvironments should be recreated in vitro. There has been a lack of microfluidic devices to support spatial and temporal stimulations in a simple and robust manner. Here, we describe a microfluidic device that generates dynamic chemical gradients and pulses in both space and time using a single device. This microfluidic device provides at least 12h of continuous stimulations that can be used to observe responses from mammalian cells. Combination of the microfluidic de-vice with live-cell imaging facilitates real-time observation of dynamic cellular response at single cell level. Using stable HEK cells with biosensors, ERK (Extracellular signal-Regulated Kinase) activities were observed un-der the pulsatile and ramping stimulations of EGF (Epidermal Growth Factor). We quantified ERK activation even at extremely low EGF concentration (0.0625µg/ml), which can not be observed using conventional techniques such as western blot. Cytoskeleton re-arrangement of the 3T3 fibroblast (stable transfection with Lifeact-GFP) was compared under abrupt and gradually changing gradient of PDGF. Copyright © 2017 Elsevier B.V. All rights reserved.

Glycolysis Is Governed by Growth Regime and Simple Enzyme Regulation in Adherent MDCK Cells

PubMed Central

Rehberg, Markus; Ritter, Joachim B.; Reichl, Udo

2014-01-01

Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses. PMID:25329309

Glycolysis is governed by growth regime and simple enzyme regulation in adherent MDCK cells.

PubMed

Rehberg, Markus; Ritter, Joachim B; Reichl, Udo

2014-10-01

Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses.

Time-resolved fluorescence microscopy to study biologically related applications using sol-gel derived and cellular media

NASA Astrophysics Data System (ADS)

Toury, Marion; Chandler, Lin; Allison, Archie; Campbell, David; McLoskey, David; Holmes-Smith, A. Sheila; Hungerford, Graham

2011-03-01

Fluorescence microscopy provides a non-invasive means for visualising dynamic protein interactions. As well as allowing the calculation of kinetic processes via the use of time-resolved fluorescence, localisation of the protein within cells or model systems can be monitored. These fluorescence lifetime images (FLIM) have become the preferred technique for elucidating protein dynamics due to the fact that the fluorescence lifetime is an absolute measure, in the main independent of fluorophore concentration and intensity fluctuations caused by factors such as photobleaching. In this work we demonstrate the use of a time-resolved fluorescence microscopy, employing a high repetition rate laser excitation source applied to study the influence of a metal surface on fluorescence tagged protein and to elucidate viscosity using the fluorescence lifetime probe DASPMI. These were studied in a cellular environment (yeast) and in a model system based on a sol-gel derived material, in which silver nanostructures were formed in situ using irradiation from a semiconductor laser in CW mode incorporated on a compact time-resolved fluorescence microscope (HORIBA Scientific DeltaDiode and DynaMyc).

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

PubMed

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Elastic force restricts growth of the murine utricle

PubMed Central

Gnedeva, Ksenia; Jacobo, Adrian; Salvi, Joshua D; Petelski, Aleksandra A; Hudspeth, A J

2017-01-01

Dysfunctions of hearing and balance are often irreversible in mammals owing to the inability of cells in the inner ear to proliferate and replace lost sensory receptors. To determine the molecular basis of this deficiency we have investigated the dynamics of growth and cellular proliferation in a murine vestibular organ, the utricle. Based on this analysis, we have created a theoretical model that captures the key features of the organ’s morphogenesis. Our experimental data and model demonstrate that an elastic force opposes growth of the utricular sensory epithelium during development, confines cellular proliferation to the organ’s periphery, and eventually arrests its growth. We find that an increase in cellular density and the subsequent degradation of the transcriptional cofactor Yap underlie this process. A reduction in mechanical constraints results in accumulation and nuclear translocation of Yap, which triggers proliferation and restores the utricle’s growth; interfering with Yap’s activity reverses this effect. DOI: http://dx.doi.org/10.7554/eLife.25681.001 PMID:28742024

Cellular characterization of compression-induceddamage in live biological samples

NASA Astrophysics Data System (ADS)

Bo, Chiara; Balzer, Jens; Hahnel, Mark; Rankin, Sara M.; Brown, Katherine A.; Proud, William

2012-03-01

Understanding the damage that high intensity compression waves induce in human tissues is critical for developing improved therapies for patients suffering from blast injuries. Experimentally based models of blast injury using live biological samples are needed. In this study we have developed a system to directly assess the effects of dynamic loading conditions on live cells. Here, we describe a confinement chamber designed to subject live cell cultures in a liquid environment to high intensity compression waves using a split Hopkinson pressure bar system. Signals from the strain gauges mounted on the bars and the chamber allow the measurement of parameters such as pressure and duration of the stimulus. The chamber itself also allows recovery of cells subjected to compression for assessment of cellular damage. In these studies we present evidence of increased levels of damage and loss of cellular integrity in cultured mouse mesenchymal stem cells subjected to a high-intensity compression wave with a peak pressure of 7.6 ± 0.8 MPa.

A systematic molecular dynamics study of nearest-neighbor effects on base pair and base pair step conformations and fluctuations in B-DNA

PubMed Central

Lavery, Richard; Zakrzewska, Krystyna; Beveridge, David; Bishop, Thomas C.; Case, David A.; Cheatham, Thomas; Dixit, Surjit; Jayaram, B.; Lankas, Filip; Laughton, Charles; Maddocks, John H.; Michon, Alexis; Osman, Roman; Orozco, Modesto; Perez, Alberto; Singh, Tanya; Spackova, Nada; Sponer, Jiri

2010-01-01

It is well recognized that base sequence exerts a significant influence on the properties of DNA and plays a significant role in protein–DNA interactions vital for cellular processes. Understanding and predicting base sequence effects requires an extensive structural and dynamic dataset which is currently unavailable from experiment. A consortium of laboratories was consequently formed to obtain this information using molecular simulations. This article describes results providing information not only on all 10 unique base pair steps, but also on all possible nearest-neighbor effects on these steps. These results are derived from simulations of 50–100 ns on 39 different DNA oligomers in explicit solvent and using a physiological salt concentration. We demonstrate that the simulations are converged in terms of helical and backbone parameters. The results show that nearest-neighbor effects on base pair steps are very significant, implying that dinucleotide models are insufficient for predicting sequence-dependent behavior. Flanking base sequences can notably lead to base pair step parameters in dynamic equilibrium between two conformational sub-states. Although this study only provides limited data on next-nearest-neighbor effects, we suggest that such effects should be analyzed before attempting to predict the sequence-dependent behavior of DNA. PMID:19850719

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Simulation of land use change in the three gorges reservoir area based on CART-CA

NASA Astrophysics Data System (ADS)

Yuan, Min

2018-05-01

This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

Crowd evacuation model based on bacterial foraging algorithm

NASA Astrophysics Data System (ADS)

Shibiao, Mu; Zhijun, Chen

To understand crowd evacuation, a model based on a bacterial foraging algorithm (BFA) is proposed in this paper. Considering dynamic and static factors, the probability of pedestrian movement is established using cellular automata. In addition, given walking and queue times, a target optimization function is built. At the same time, a BFA is used to optimize the objective function. Finally, through real and simulation experiments, the relationship between the parameters of evacuation time, exit width, pedestrian density, and average evacuation speed is analyzed. The results show that the model can effectively describe a real evacuation.

Part 3 Specialized aspects of GIS and spatial analysis . Garage band science and dynamic spatial models

NASA Astrophysics Data System (ADS)

Box, Paul W.

GIS and spatial analysis is suited mainly for static pictures of the landscape, but many of the processes that need exploring are dynamic in nature. Dynamic processes can be complex when put in a spatial context; our ability to study such processes will probably come with advances in understanding complex systems in general. Cellular automata and agent-based models are two prime candidates for exploring complex spatial systems, but are difficult to implement. Innovative tools that help build complex simulations will create larger user communities, who will probably find novel solutions for understanding complexity. A significant source for such innovations is likely to be from the collective efforts of hobbyists and part-time programmers, who have been dubbed ``garage-band scientists'' in the popular press.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm

PubMed Central

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-01-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology. DOI: http://dx.doi.org/10.7554/eLife.19274.001 PMID:27801646

A dynamic cellular vertex model of growing epithelial tissues

NASA Astrophysics Data System (ADS)

Lin, Shao-Zhen; Li, Bo; Feng, Xi-Qiao

2017-04-01

Intercellular interactions play a significant role in a wide range of biological functions and processes at both the cellular and tissue scales, for example, embryogenesis, organogenesis, and cancer invasion. In this paper, a dynamic cellular vertex model is presented to study the morphomechanics of a growing epithelial monolayer. The regulating role of stresses in soft tissue growth is revealed. It is found that the cells originating from the same parent cell in the monolayer can orchestrate into clustering patterns as the tissue grows. Collective cell migration exhibits a feature of spatial correlation across multiple cells. Dynamic intercellular interactions can engender a variety of distinct tissue behaviors in a social context. Uniform cell proliferation may render high and heterogeneous residual compressive stresses, while stress-regulated proliferation can effectively release the stresses, reducing the stress heterogeneity in the tissue. The results highlight the critical role of mechanical factors in the growth and morphogenesis of epithelial tissues and help understand the development and invasion of epithelial tumors.

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

PubMed Central

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-01-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications. PMID:26525841

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope.

PubMed

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-03

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

Mapping the dynamics of force transduction at cell–cell junctions of epithelial clusters

PubMed Central

Ng, Mei Rosa; Besser, Achim; Brugge, Joan S; Danuser, Gaudenz

2014-01-01

Force transduction at cell-cell adhesions regulates tissue development, maintenance and adaptation. We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters. Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell-cell junctions. At the multi-cellular scale, cell-cell force exchange depended on the cell position within a cluster, and was adaptive to reconfigurations due to cell divisions or positional rearrangements. Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors. These data provide insights into mechanisms that could control mechanical stress homeostasis in dynamic epithelial tissues, and highlight our methods as a resource for the study of mechanotransduction in cell-cell adhesions. DOI: http://dx.doi.org/10.7554/eLife.03282.001 PMID:25479385

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

NASA Astrophysics Data System (ADS)

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

Optimization of industrial microorganisms: recent advances in synthetic dynamic regulators.

PubMed

Min, Byung Eun; Hwang, Hyun Gyu; Lim, Hyun Gyu; Jung, Gyoo Yeol

2017-01-01

Production of biochemicals by industrial fermentation using microorganisms requires maintaining cellular production capacity, because maximal productivity is economically important. High-productivity microbial strains can be developed using static engineering, but these may not maintain maximal productivity throughout the culture period as culture conditions and cell states change dynamically. Additionally, economic reasons limit heterologous protein expression using inducible promoters to prevent metabolic burden for commodity chemical and biofuel production. Recently, synthetic and systems biology has been used to design genetic circuits, precisely controlling gene expression or influencing genetic behavior toward a desired phenotype. Development of dynamic regulators can maintain cellular phenotype in a maximum production state in response to factors including cell concentration, oxygen, temperature, pH, and metabolites. Herein, we introduce dynamic regulators of industrial microorganism optimization and discuss metabolic flux fine control by dynamic regulators in response to metabolites or extracellular stimuli, robust production systems, and auto-induction systems using quorum sensing.

Time, space, and disorder in the expanding proteome universe.

PubMed

Minde, David-Paul; Dunker, A Keith; Lilley, Kathryn S

2017-04-01

Proteins are highly dynamic entities. Their myriad functions require specific structures, but proteins' dynamic nature ranges all the way from the local mobility of their amino acid constituents to mobility within and well beyond single cells. A truly comprehensive view of the dynamic structural proteome includes: (i) alternative sequences, (ii) alternative conformations, (iii) alternative interactions with a range of biomolecules, (iv) cellular localizations, (v) alternative behaviors in different cell types. While these aspects have traditionally been explored one protein at a time, we highlight recently emerging global approaches that accelerate comprehensive insights into these facets of the dynamic nature of protein structure. Computational tools that integrate and expand on multiple orthogonal data types promise to enable the transition from a disjointed list of static snapshots to a structurally explicit understanding of the dynamics of cellular mechanisms. © 2017 The Authors. Proteomics Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Perspective: A Dynamics-Based Classification of Ventricular Arrhythmias

PubMed Central

Weiss, James N.; Garfinkel, Alan; Karagueuzian, Hrayr S.; Nguyen, Thao P.; Olcese, Riccardo; Chen, Peng-Sheng; Qu, Zhilin

2015-01-01

Despite key advances in the clinical management of life-threatening ventricular arrhythmias, culminating with the development of implantable cardioverter-defibrillators and catheter ablation techniques, pharmacologic/biologic therapeutics have lagged behind. The fundamental issue is that biological targets are molecular factors. Diseases, however, represent emergent properties at the scale of the organism that result from dynamic interactions between multiple constantly changing molecular factors. For a pharmacologic/biologic therapy to be effective, it must target the dynamic processes that underlie the disease. Here we propose a classification of ventricular arrhythmias that is based on our current understanding of the dynamics occurring at the subcellular, cellular, tissue and organism scales, which cause arrhythmias by simultaneously generating arrhythmia triggers and exacerbating tissue vulnerability. The goal is to create a framework that systematically links these key dynamic factors together with fixed factors (structural and electrophysiological heterogeneity) synergistically promoting electrical dispersion and increased arrhythmia risk to molecular factors that can serve as biological targets. We classify ventricular arrhythmias into three primary dynamic categories related generally to unstable Ca cycling, reduced repolarization, and excess repolarization, respectively. The clinical syndromes, arrhythmia mechanisms, dynamic factors and what is known about their molecular counterparts are discussed. Based on this framework, we propose a computational-experimental strategy for exploring the links between molecular factors, fixed factors and dynamic factors that underlie life-threatening ventricular arrhythmias. The ultimate objective is to facilitate drug development by creating an in silico platform to evaluate and predict comprehensively how molecular interventions affect not only a single targeted arrhythmia, but all primary arrhythmia dynamics categories as well as normal cardiac excitation-contraction coupling. PMID:25769672

Simulation tools for particle-based reaction-diffusion dynamics in continuous space

PubMed Central

2014-01-01

Particle-based reaction-diffusion algorithms facilitate the modeling of the diffusional motion of individual molecules and the reactions between them in cellular environments. A physically realistic model, depending on the system at hand and the questions asked, would require different levels of modeling detail such as particle diffusion, geometrical confinement, particle volume exclusion or particle-particle interaction potentials. Higher levels of detail usually correspond to increased number of parameters and higher computational cost. Certain systems however, require these investments to be modeled adequately. Here we present a review on the current field of particle-based reaction-diffusion software packages operating on continuous space. Four nested levels of modeling detail are identified that capture incrementing amount of detail. Their applicability to different biological questions is discussed, arching from straight diffusion simulations to sophisticated and expensive models that bridge towards coarse grained molecular dynamics. PMID:25737778

Integrated experimental and model-based analysis reveals the spatial aspects of EGFR activation dynamics

PubMed Central

Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. Steven; Resat, Haluk

2012-01-01

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models to determine the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor phosphorylation kinetics at the cell surface and early endosomes are comparable. We validated the last finding by measuring the EGFR dephosphorylation rates at various times following ligand addition both in whole cells and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks. PMID:22952062

Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution†

PubMed Central

Johnson-Chavarria, Eric M.; Agrawal, Utsav; Tanyeri, Melikhan; Kuhlman, Thomas E.

2014-01-01

We report an automated microfluidic-based platform for single cell analysis that allows for cell culture in free solution with the ability to control the cell growth environment. Using this approach, cells are confined by the sole action of gentle fluid flow, thereby enabling non-perturbative analysis of cell growth away from solid boundaries. In addition, the single cell microbioreactor allows for precise and time-dependent control over cell culture media, with the combined ability to observe the dynamics of non-adherent cells over long time scales. As a proof-of-principle demonstration, we used the platform to observe dynamic cell growth, gene expression, and intracellular diffusion of repressor proteins while precisely tuning the cell growth environment. Overall, this microfluidic approach enables the direct observation of cellular dynamics with exquisite control over environmental conditions, which will be useful for quantifying the behaviour of single cells in well-defined media. PMID:24836754

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

In Vitro Experimental Model for the Long-Term Analysis of Cellular Dynamics During Bronchial Tree Development from Lung Epithelial Cells

PubMed Central

Maruta, Naomichi; Marumoto, Moegi

2017-01-01

Lung branching morphogenesis has been studied for decades, but the underlying developmental mechanisms are still not fully understood. Cellular movements dynamically change during the branching process, but it is difficult to observe long-term cellular dynamics by in vivo or tissue culture experiments. Therefore, developing an in vitro experimental model of bronchial tree would provide an essential tool for developmental biology, pathology, and systems biology. In this study, we succeeded in reconstructing a bronchial tree in vitro by using primary human bronchial epithelial cells. A high concentration gradient of bronchial epithelial cells was required for branching initiation, whereas homogeneously distributed endothelial cells induced the formation of successive branches. Subsequently, the branches grew in size to the order of millimeter. The developed model contains only two types of cells and it facilitates the analysis of lung branching morphogenesis. By taking advantage of our experimental model, we carried out long-term time-lapse observations, which revealed self-assembly, collective migration with leader cells, rotational motion, and spiral motion of epithelial cells in each developmental event. Mathematical simulation was also carried out to analyze the self-assembly process and it revealed simple rules that govern cellular dynamics. Our experimental model has provided many new insights into lung development and it has the potential to accelerate the study of developmental mechanisms, pattern formation, left–right asymmetry, and disease pathogenesis of the human lung. PMID:28471293

Dynamical analysis of cellular ageing by modeling of gene regulatory network based attractor landscape.

PubMed

Chong, Ket Hing; Zhang, Xiaomeng; Zheng, Jie

2018-01-01

Ageing is a natural phenomenon that is inherently complex and remains a mystery. Conceptual model of cellular ageing landscape was proposed for computational studies of ageing. However, there is a lack of quantitative model of cellular ageing landscape. This study aims to investigate the mechanism of cellular ageing in a theoretical model using the framework of Waddington's epigenetic landscape. We construct an ageing gene regulatory network (GRN) consisting of the core cell cycle regulatory genes (including p53). A model parameter (activation rate) is used as a measure of the accumulation of DNA damage. Using the bifurcation diagrams to estimate the parameter values that lead to multi-stability, we obtained a conceptual model for capturing three distinct stable steady states (or attractors) corresponding to homeostasis, cell cycle arrest, and senescence or apoptosis. In addition, we applied a Monte Carlo computational method to quantify the potential landscape, which displays: I) one homeostasis attractor for low accumulation of DNA damage; II) two attractors for cell cycle arrest and senescence (or apoptosis) in response to high accumulation of DNA damage. Using the Waddington's epigenetic landscape framework, the process of ageing can be characterized by state transitions from landscape I to II. By in silico perturbations, we identified the potential landscape of a perturbed network (inactivation of p53), and thereby demonstrated the emergence of a cancer attractor. The simulated dynamics of the perturbed network displays a landscape with four basins of attraction: homeostasis, cell cycle arrest, senescence (or apoptosis) and cancer. Our analysis also showed that for the same perturbed network with low DNA damage, the landscape displays only the homeostasis attractor. The mechanistic model offers theoretical insights that can facilitate discovery of potential strategies for network medicine of ageing-related diseases such as cancer.

Approaches to simulating the “March of Bricks and Mortar”

USGS Publications Warehouse

Goldstein, Noah Charles; Candau, J.T.; Clarke, K.C.

2004-01-01

Re-creation of the extent of urban land use at different periods in time is valuable for examining how cities grow and how policy changes influence urban dynamics. To date, there has been little focus on the modeling of historical urban extent (other than for ancient cities). Instead, current modeling research has emphasized simulating the cities of the future. Predictive models can provide insights into urban growth processes and are valuable for land-use and urban planners, yet historical trends are largely ignored. This is unfortunate since historical data exist for urban areas and can be used to quantitatively test dynamic models and theory. We maintain that understanding the growth dynamics of a region's past allows more intelligent forecasts of its future. We compare using a spatio-temporal interpolation method with an agent-based simulation approach to recreate the urban extent of Santa Barbara, California, annually from 1929 to 2001. The first method uses current yet incomplete data on the construction of homes in the region. The latter uses a Cellular Automata based model, SLEUTH, to back- or hind-cast the urban extent. The success at historical urban growth reproduction of the two approaches used in this work was quantified for comparison. The performance of each method is described, as well as the utility of each model in re-creating the history of Santa Barbara. Additionally, the models’ assumptions about space are contrasted. As a consequence, we propose that both approaches are useful in historical urban simulations, yet the cellular approach is more flexible as it can be extended for spatio-temporal extrapolation.

Cellular burdens and biological effects on tissue level caused by inhaled radon progenies.

PubMed

Madas, B G; Balásházy, I; Farkas, Á; Szoke, I

2011-02-01

In the case of radon exposure, the spatial distribution of deposited radioactive particles is highly inhomogeneous in the central airways. The object of this research is to investigate the consequences of this heterogeneity regarding cellular burdens in the bronchial epithelium and to study the possible biological effects at tissue level. Applying computational fluid and particle dynamics techniques, the deposition distribution of inhaled radon daughters has been determined in a bronchial airway model for 23 min of work in the New Mexico uranium mine corresponding to 0.0129 WLM exposure. A numerical epithelium model based on experimental data has been utilised in order to quantify cellular hits and doses. Finally, a carcinogenesis model considering cell death-induced cell-cycle shortening has been applied to assess the biological responses. Present computations reveal that cellular dose may reach 1.5 Gy, which is several orders of magnitude higher than tissue dose. The results are in agreement with the histological finding that the uneven deposition distribution of radon progenies may lead to inhomogeneous spatial distribution of tumours in the bronchial airways. In addition, at the macroscopic level, the relationship between cancer risk and radiation burden seems to be non-linear.

A stochastic cellular automata model of tautomer equilibria

NASA Astrophysics Data System (ADS)

Bowers, Gregory A.; Seybold, Paul G.

2018-03-01

Many chemical substances, including drugs and biomolecules, exist in solution not as a single species, but as a collection of tautomers and related species. Importantly, each of these species is an independent compoundwith its own specific biochemical and physicochemical properties. The species interconvert in a dynamic and often complicated manner, making modelling the overall species composition difficult. Agent-based cellular automata models are uniquely suited to meet this challenge, allowing the equilibria to be simulated using simple rulesand at the same time capturing the inherent stochasticity of the natural phenomenon. In the present example a stochastic cellular automata model is employed to simulate the tautomer equilibria of 9-anthrone and 9-anthrol in the presence of their common anion. The observed KE of the 9-anthrone ⇌ 9-anthrol tautomerisation along with the measured tautomer pKa values were used to model the equilibria at pH values 4, 7 and 10. At pH 4 and 7, the anthrone comprises >99% of the total species population, while at pH 10the anthrone and the anion each represent just under half of the total population. The advantages of the cellular automata approach over the customary coupled differential equation approach are discussed.

In vivo cell biology in zebrafish – providing insights into vertebrate development and disease

PubMed Central

Vacaru, Ana M.; Unlu, Gokhan; Spitzner, Marie; Mione, Marina; Knapik, Ela W.; Sadler, Kirsten C.

2014-01-01

ABSTRACT Over the past decades, studies using zebrafish have significantly advanced our understanding of the cellular basis for development and human diseases. Zebrafish have rapidly developing transparent embryos that allow comprehensive imaging of embryogenesis combined with powerful genetic approaches. However, forward genetic screens in zebrafish have generated unanticipated findings that are mirrored by human genetic studies: disruption of genes implicated in basic cellular processes, such as protein secretion or cytoskeletal dynamics, causes discrete developmental or disease phenotypes. This is surprising because many processes that were assumed to be fundamental to the function and survival of all cell types appear instead to be regulated by cell-specific mechanisms. Such discoveries are facilitated by experiments in whole animals, where zebrafish provides an ideal model for visualization and manipulation of organelles and cellular processes in a live vertebrate. Here, we review well-characterized mutants and newly developed tools that underscore this notion. We focus on the secretory pathway and microtubule-based trafficking as illustrative examples of how studying cell biology in vivo using zebrafish has broadened our understanding of the role fundamental cellular processes play in embryogenesis and disease. PMID:24481493

Protein Corona Analysis of Silver Nanoparticles Links to Their Cellular Effects.

PubMed

Juling, Sabine; Niedzwiecka, Alicia; Böhmert, Linda; Lichtenstein, Dajana; Selve, Sören; Braeuning, Albert; Thünemann, Andreas F; Krause, Eberhard; Lampen, Alfonso

2017-11-03

The breadth of applications of nanoparticles and the access to food-associated consumer products containing nanosized materials lead to oral human exposure to such particles. In biological fluids nanoparticles dynamically interact with biomolecules and form a protein corona. Knowledge about the protein corona is of great interest for understanding the molecular effects of particles as well as their fate inside the human body. We used a mass spectrometry-based toxicoproteomics approach to elucidate mechanisms of toxicity of silver nanoparticles and to comprehensively characterize the protein corona formed around silver nanoparticles in Caco-2 human intestinal epithelial cells. Results were compared with respect to the cellular function of proteins either affected by exposure to nanoparticles or present in the protein corona. A transcriptomic data set was included in the analyses in order to obtain a combined multiomics view of nanoparticle-affected cellular processes. A relationship between corona proteins and the proteomic or transcriptomic responses was revealed, showing that differentially regulated proteins or transcripts were engaged in the same cellular signaling pathways. Protein corona analyses of nanoparticles in cells might therefore help in obtaining information about the molecular consequences of nanoparticle treatment.

Reprogramming cancer cells: a novel approach for cancer therapy or a tool for disease-modeling?

PubMed

Yilmazer, Açelya; de Lázaro, Irene; Taheri, Hadiseh

2015-12-01

Chromatin dynamics have been the major focus of many physiological and pathological processes over the past 20 years. Epigenetic mechanisms have been shown to be reshaped during both cellular reprogramming and tumorigenesis. For this reason, cancer cell reprogramming can provide a powerful tool to better understand both regenerative and cancer-fate processes, with a potential to develop novel therapeutic approaches. Recent studies showed that cancer cells can be reprogrammed to a pluripotent state by the overexpression of reprogramming transcription factors. Activation of transcription factors and modification of chromatin regulators may result in the remodeling of epigenetic status and refueling of tumorigenicity in these reprogrammed cancer cells. However, studies focusing on cancer cell reprogramming are contradictory; some studies reported increased tumor progression whereas others showed that cellular reprogramming has a treatment potential for cancer. In this review, first, the current knowledge on the epigenetic mechanisms involved during cancer development and cellular reprogramming will be presented. Later, different reports and key factors about pluripotency-based reprogramming of cancer cells will be reviewed in detail. New insights will be provided on cancer biology and therapy in the light of cellular reprogramming. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Rho GTPases at the crossroad of signaling networks in mammals: impact of Rho-GTPases on microtubule organization and dynamics.

PubMed

Wojnacki, José; Quassollo, Gonzalo; Marzolo, María-Paz; Cáceres, Alfredo

2014-01-01

Microtubule (MT) organization and dynamics downstream of external cues is crucial for maintaining cellular architecture and the generation of cell asymmetries. In interphase cells RhoA, Rac, and Cdc42, conspicuous members of the family of small Rho GTPases, have major roles in modulating MT stability, and hence polarized cell behaviors. However, MTs are not mere targets of Rho GTPases, but also serve as signaling platforms coupling MT dynamics to Rho GTPase activation in a variety of cellular conditions. In this article, we review some of the key studies describing the reciprocal relationship between small Rho-GTPases and MTs during migration and polarization.

Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.

PubMed

Precharattana, Monamorn

2016-02-01

Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.

Crowding in Cellular Environments at an Atomistic Level from Computer Simulations

PubMed Central

2017-01-01

The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments. PMID:28666087

A Fast Microfluidic Temperature Control Device for Studying Microtubule Dynamics in Fission Yeast

PubMed Central

Velve-Casquillas, Guilhem; Costa, Judite; Carlier-Grynkorn, Frédérique; Mayeux, Adeline; Tran, Phong T.

2010-01-01

Recent development in soft lithography and microfluidics enables biologists to create tools to control the cellular microenvironment. One such control is the ability to quickly change the temperature of the cells. Genetic model organism such as fission yeast has been useful for studies of the cell cytoskeleton. In particular, the dynamic microtubule cytoskeleton responds to changes in temperature. In addition, there are temperature-sensitive mutations of cytoskeletal proteins. We describe here the fabrication and use of a microfluidic device to quickly and reversibly change cellular temperature between 2°C and 50°C. We demonstrate the use of this device while imaging at high-resolution microtubule dynamics in fission yeast. PMID:20719272

Experimental design for dynamics identification of cellular processes.

PubMed

Dinh, Vu; Rundell, Ann E; Buzzard, Gregery T

2014-03-01

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.M. Donahue et al. (IET Syst. Biol. 4:249-262, 2010). In this approach, existing data is used to define a probability distribution on the parameters; the next measurement point is the one that yields the largest model output variance with this distribution. Building upon this approach, we introduce the Expected Dynamics Estimator (EDE), which is the expected value using this distribution of the output as a function of time. We prove the consistency of this estimator (uniform convergence to true dynamics) even when the chosen experiments cluster in a finite set of points. We extend this proof of consistency to various practical assumptions on noisy data and moderate levels of model mismatch. Through the derivation and proof, we develop a relaxed version of MINE that is more computationally tractable and robust than the original formulation. The results are illustrated with numerical examples on two nonlinear ordinary differential equation models of biomolecular and cellular processes.

Far-field photostable optical nanoscopy (PHOTON) for real-time super-resolution single-molecular imaging of signaling pathways of single live cells

NASA Astrophysics Data System (ADS)

Huang, Tao; Browning, Lauren M.; Xu, Xiao-Hong Nancy

2012-04-01

Cellular signaling pathways play crucial roles in cellular functions and design of effective therapies. Unfortunately, study of cellular signaling pathways remains formidably challenging because sophisticated cascades are involved, and a few molecules are sufficient to trigger signaling responses of a single cell. Here we report the development of far-field photostable-optical-nanoscopy (PHOTON) with photostable single-molecule-nanoparticle-optical-biosensors (SMNOBS) for mapping dynamic cascades of apoptotic signaling pathways of single live cells in real-time at single-molecule (SM) and nanometer (nm) resolutions. We have quantitatively imaged single ligand molecules (tumor necrosis factor α, TNFα) and their binding kinetics with their receptors (TNFR1) on single live cells; tracked formation and internalization of their clusters and their initiation of intracellular signaling pathways in real-time; and studied apoptotic signaling dynamics and mechanisms of single live cells with sufficient temporal and spatial resolutions. This study provides new insights into complex real-time dynamic cascades and molecular mechanisms of apoptotic signaling pathways of single live cells. PHOTON provides superior imaging and sensing capabilities and SMNOBS offer unrivaled biocompatibility and photostability, which enable probing of signaling pathways of single live cells in real-time at SM and nm resolutions.Cellular signaling pathways play crucial roles in cellular functions and design of effective therapies. Unfortunately, study of cellular signaling pathways remains formidably challenging because sophisticated cascades are involved, and a few molecules are sufficient to trigger signaling responses of a single cell. Here we report the development of far-field photostable-optical-nanoscopy (PHOTON) with photostable single-molecule-nanoparticle-optical-biosensors (SMNOBS) for mapping dynamic cascades of apoptotic signaling pathways of single live cells in real-time at single-molecule (SM) and nanometer (nm) resolutions. We have quantitatively imaged single ligand molecules (tumor necrosis factor α, TNFα) and their binding kinetics with their receptors (TNFR1) on single live cells; tracked formation and internalization of their clusters and their initiation of intracellular signaling pathways in real-time; and studied apoptotic signaling dynamics and mechanisms of single live cells with sufficient temporal and spatial resolutions. This study provides new insights into complex real-time dynamic cascades and molecular mechanisms of apoptotic signaling pathways of single live cells. PHOTON provides superior imaging and sensing capabilities and SMNOBS offer unrivaled biocompatibility and photostability, which enable probing of signaling pathways of single live cells in real-time at SM and nm resolutions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr11739h

Fast, label-free super-resolution live-cell imaging using rotating coherent scattering (ROCS) microscopy

NASA Astrophysics Data System (ADS)

Jünger, Felix; Olshausen, Philipp V.; Rohrbach, Alexander

2016-07-01

Living cells are highly dynamic systems with cellular structures being often below the optical resolution limit. Super-resolution microscopes, usually based on fluorescence cell labelling, are usually too slow to resolve small, dynamic structures. We present a label-free microscopy technique, which can generate thousands of super-resolved, high contrast images at a frame rate of 100 Hertz and without any post-processing. The technique is based on oblique sample illumination with coherent light, an approach believed to be not applicable in life sciences because of too many interference artefacts. However, by circulating an incident laser beam by 360° during one image acquisition, relevant image information is amplified. By combining total internal reflection illumination with dark-field detection, structures as small as 150 nm become separable through local destructive interferences. The technique images local changes in refractive index through scattered laser light and is applied to living mouse macrophages and helical bacteria revealing unexpected dynamic processes.

Fast, label-free super-resolution live-cell imaging using rotating coherent scattering (ROCS) microscopy

PubMed Central

Jünger, Felix; Olshausen, Philipp v.; Rohrbach, Alexander

2016-01-01

Living cells are highly dynamic systems with cellular structures being often below the optical resolution limit. Super-resolution microscopes, usually based on fluorescence cell labelling, are usually too slow to resolve small, dynamic structures. We present a label-free microscopy technique, which can generate thousands of super-resolved, high contrast images at a frame rate of 100 Hertz and without any post-processing. The technique is based on oblique sample illumination with coherent light, an approach believed to be not applicable in life sciences because of too many interference artefacts. However, by circulating an incident laser beam by 360° during one image acquisition, relevant image information is amplified. By combining total internal reflection illumination with dark-field detection, structures as small as 150 nm become separable through local destructive interferences. The technique images local changes in refractive index through scattered laser light and is applied to living mouse macrophages and helical bacteria revealing unexpected dynamic processes. PMID:27465033

The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

PubMed

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T

2008-02-29

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations.

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

PubMed Central

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T.

2008-01-01

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations. PMID:18463702

Patterning pallet arrays for cell selection based on high-resolution measurements of fluorescent biosensors

PubMed Central

Shadpour, Hamed; Zawistowski, Jon S.; Herman, Annadele; Hahn, Klaus; Allbritton, Nancy L.

2011-01-01

Pallet arrays enable cells to be separated while they remain adherent to a surface and provide a much greater range of cell selection criteria relative to that of current technologies. However there remains a need to further broaden cell selection criteria to include dynamic intracellular signaling events. To demonstrate the feasibility of measuring cellular protein behavior on the arrays using high resolution microscopy, the surfaces of individual pallets were modified to minimize the impact of scattered light at the pallet edges. The surfaces of the three-dimensional pallets on an array were patterned with a coating such as fibronectin using a customized stamping tool. Micropatterns of varying shape and size were printed in designated regions on the pallets in single or multiple steps to demonstrate the reliability and precision of patterning molecules on the pallet surface. Use of a fibronectin matrix stamped at the center of each pallet permitted the localization of H1299 and mouse embryonic fibroblast (MEF) cells to the pallet centers and away from the edges. Compared to pallet arrays with fibronection coating the entire top surface, arrays with a central fibronectin pattern increased the percentage of cells localized to the pallet center by 3-4 fold. Localization of cells to the pallet center also enabled the physical separation of cells from optical artifacts created by the rough pallet side walls. To demonstrate the measurement of dynamic intracellular signaling on the arrays, fluorescence measurements of high spatial resolution were performed using a RhoA GTPase biosensor. This biosensor utilized fluorescence resonance energy transfer (FRET) between cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP) to measure localized RhoA activity in cellular ruffles at the cell periphery. These results demonstrated the ability to perform spatially resolved measurements of fluorescence-based sensors on the pallet arrays. Thus, the patterned pallet arrays should enable novel cell separations in which cell selection is based on complex cellular signaling properties. PMID:21621038

The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks.

PubMed

Landau, Itamar D; Egger, Robert; Dercksen, Vincent J; Oberlaender, Marcel; Sompolinsky, Haim

2016-12-07

Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hofstetter, Markus; Howgate, John; Schmid, Martin

Highlights: Black-Right-Pointing-Pointer Gallium nitride based sensors show promising characteristics to monitor cellular parameters. Black-Right-Pointing-Pointer Cell growth experiments reveal excellent biocompatibiltiy of the host GaN material. Black-Right-Pointing-Pointer We present a biofunctionality assay using ionizing radiation. Black-Right-Pointing-Pointer DNA repair is utilized to evaluate material induced alterations in the cellular behavior. Black-Right-Pointing-Pointer GaN shows no bio-functional influence on the cellular environment. -- Abstract: There is an increasing interest in the integration of hybrid bio-semiconductor systems for the non-invasive evaluation of physiological parameters. High quality gallium nitride and its alloys show promising characteristics to monitor cellular parameters. Nevertheless, such applications not only request appropriatemore » sensing capabilities but also the biocompatibility and especially the biofunctionality of materials. Here we show extensive biocompatibility studies of gallium nitride and, for the first time, a biofunctionality assay using ionizing radiation. Analytical sensor devices are used in medical settings, as well as for cell- and tissue engineering. Within these fields, semiconductor devices have increasingly been applied for online biosensing on a cellular and tissue level. Integration of advanced materials such as gallium nitride into these systems has the potential to increase the range of applicability for a multitude of test devices and greatly enhance sensitivity and functionality. However, for such applications it is necessary to optimize cell-surface interactions and to verify the biocompatibility of the semiconductor. In this work, we present studies of mouse fibroblast cell activity grown on gallium nitride surfaces after applying external noxa. Cell-semiconductor hybrids were irradiated with X-rays at air kerma doses up to 250 mGy and the DNA repair dynamics, cell proliferation, and cell growth dynamics of adherent cells were compared to control samples. The impact of ionizing radiation on DNA, along with the associated cellular repair mechanisms, is well characterized and serves as a reference tool for evaluation of substrate effects. The results indicate that gallium nitride does not require specific surface treatments to ensure biocompatibility and suggest that cell signaling is not affected by micro-environmental alterations arising from gallium nitride-cell interactions. The observation that gallium nitride provides no bio-functional influence on the cellular environment confirms that this material is well suited for future biosensing applications without the need for additional chemical surface modification.« less

The use of many-body physics and thermodynamics to describe the dynamics of rhythmic generators in sensory cortices engaged in memory and learning.

PubMed

Vitiello, Giuseppe

2015-04-01

The problem of the transition from the molecular and cellular level to the macroscopic level of observed assemblies of myriads of neurons is the subject addressed in this report. The great amount of detailed information available at molecular and cellular level seems not sufficient to account for the high effectiveness and reliability observed in the brain macroscopic functioning. It is suggested that the dissipative many-body model and thermodynamics might offer the dynamical frame underlying the rich phenomenology observed at microscopic and macroscopic level and help in the understanding on how to fill the gap between the bio-molecular and cellular level and the one of brain macroscopic functioning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Autophagy capacity and sub-mitochondrial heterogeneity shape Bnip3-induced mitophagy regulation of apoptosis.

PubMed

Choe, Sehyo Charley; Hamacher-Brady, Anne; Brady, Nathan Ryan

2015-08-08

Mitochondria are key regulators of apoptosis. In response to stress, BH3-only proteins activate pro-apoptotic Bcl2 family proteins Bax and Bak, which induce mitochondrial outer membrane permeabilization (MOMP). While the large-scale mitochondrial release of pro-apoptotic proteins activates caspase-dependent cell death, a limited release results in sub-lethal caspase activation which promotes tumorigenesis. Mitochondrial autophagy (mitophagy) targets dysfunctional mitochondria for degradation by lysosomes, and undergoes extensive crosstalk with apoptosis signaling, but its influence on apoptosis remains undetermined. The BH3-only protein Bnip3 integrates apoptosis and mitophagy signaling at different signaling domains. Bnip3 inhibits pro-survival Bcl2 members via its BH3 domain and activates mitophagy through its LC3 Interacting Region (LIR), which is responsible for binding to autophagosomes. Previously, we have shown that Bnip3-activated mitophagy prior to apoptosis induction can reduce mitochondrial activation of caspases, suggesting that a reduction to mitochondrial levels may be pro-survival. An outstanding question is whether organelle dynamics and/or recently discovered subcellular variations of protein levels responsible for both MOMP sensitivity and crosstalk between apoptosis and mitophagy can influence the cellular apoptosis decision event. To that end, here we undertook a systems biology analysis of mitophagy-apoptosis crosstalk at the level of cellular mitochondrial populations. Based on experimental findings, we developed a multi-scale, hybrid model with an individually adaptive mitochondrial population, whose actions are determined by protein levels, embedded in an agent-based model (ABM) for simulating subcellular dynamics and local feedback via reactive oxygen species signaling. Our model, supported by experimental evidence, identified an emergent regulatory structure within canonical apoptosis signaling. We show that the extent of mitophagy is determined by levels and spatial localization of autophagy capacity, and subcellular mitochondrial protein heterogeneities. Our model identifies mechanisms and conditions that alter the mitophagy decision within mitochondrial subpopulations to an extent sufficient to shape cellular outcome to apoptotic stimuli. Overall, our modeling approach provides means to suggest new experiments and implement findings at multiple scales in order to understand how network topologies and subcellular heterogeneities can influence signaling events at individual organelle level, and hence, determine the emergence of heterogeneity in cellular decisions due the actions of the collective intra-cellular population.

Octree-based, GPU implementation of a continuous cellular automaton for the simulation of complex, evolving surfaces

NASA Astrophysics Data System (ADS)

Ferrando, N.; Gosálvez, M. A.; Cerdá, J.; Gadea, R.; Sato, K.

2011-03-01

Presently, dynamic surface-based models are required to contain increasingly larger numbers of points and to propagate them over longer time periods. For large numbers of surface points, the octree data structure can be used as a balance between low memory occupation and relatively rapid access to the stored data. For evolution rules that depend on neighborhood states, extended simulation periods can be obtained by using simplified atomistic propagation models, such as the Cellular Automata (CA). This method, however, has an intrinsic parallel updating nature and the corresponding simulations are highly inefficient when performed on classical Central Processing Units (CPUs), which are designed for the sequential execution of tasks. In this paper, a series of guidelines is presented for the efficient adaptation of octree-based, CA simulations of complex, evolving surfaces into massively parallel computing hardware. A Graphics Processing Unit (GPU) is used as a cost-efficient example of the parallel architectures. For the actual simulations, we consider the surface propagation during anisotropic wet chemical etching of silicon as a computationally challenging process with a wide-spread use in microengineering applications. A continuous CA model that is intrinsically parallel in nature is used for the time evolution. Our study strongly indicates that parallel computations of dynamically evolving surfaces simulated using CA methods are significantly benefited by the incorporation of octrees as support data structures, substantially decreasing the overall computational time and memory usage.

Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks

PubMed Central

Lu, Zhaoming; Pan, Qi; Wang, Luhan; Wen, Xiangming

2016-01-01

Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network. PMID:27936011

Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks.

PubMed

Lu, Zhaoming; Pan, Qi; Wang, Luhan; Wen, Xiangming

2016-01-01

Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network.

An improved cellular automata model for train operation simulation with dynamic acceleration

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

An individual-based modeling approach to simulate the effects of cellular nutrient competition on Escherichia coli K-12 MG1655 colony behavior and interactions in aerobic structured food systems.

PubMed

Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M

2015-02-01

Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

S-nitrosylation drives cell senescence and aging in mammals by controlling mitochondrial dynamics and mitophagy.

PubMed

Rizza, Salvatore; Cardaci, Simone; Montagna, Costanza; Di Giacomo, Giuseppina; De Zio, Daniela; Bordi, Matteo; Maiani, Emiliano; Campello, Silvia; Borreca, Antonella; Puca, Annibale A; Stamler, Jonathan S; Cecconi, Francesco; Filomeni, Giuseppe

2018-04-10

S -nitrosylation, a prototypic redox-based posttranslational modification, is frequently dysregulated in disease. S -nitrosoglutathione reductase (GSNOR) regulates protein S -nitrosylation by functioning as a protein denitrosylase. Deficiency of GSNOR results in tumorigenesis and disrupts cellular homeostasis broadly, including metabolic, cardiovascular, and immune function. Here, we demonstrate that GSNOR expression decreases in primary cells undergoing senescence, as well as in mice and humans during their life span. In stark contrast, exceptionally long-lived individuals maintain GSNOR levels. We also show that GSNOR deficiency promotes mitochondrial nitrosative stress, including excessive S -nitrosylation of Drp1 and Parkin, thereby impairing mitochondrial dynamics and mitophagy. Our findings implicate GSNOR in mammalian longevity, suggest a molecular link between protein S -nitrosylation and mitochondria quality control in aging, and provide a redox-based perspective on aging with direct therapeutic implications.

Toxicological Tipping Points: Learning Boolean Networks from High-Content Imaging Data. (BOSC meeting)

EPA Science Inventory

The objective of this work is to elucidate biological networks underlying cellular tipping points using time-course data. We discretized the high-content imaging (HCI) data and inferred Boolean networks (BNs) that could accurately predict dynamic cellular trajectories. We found t...

Engineering cellular fibers for musculoskeletal soft tissues using directed self-assembly.

PubMed

Schiele, Nathan R; Koppes, Ryan A; Chrisey, Douglas B; Corr, David T

2013-05-01

Engineering strategies guided by developmental biology may enhance and accelerate in vitro tissue formation for tissue engineering and regenerative medicine applications. In this study, we looked toward embryonic tendon development as a model system to guide our soft tissue engineering approach. To direct cellular self-assembly, we utilized laser micromachined, differentially adherent growth channels lined with fibronectin. The micromachined growth channels directed human dermal fibroblast cells to form single cellular fibers, without the need for a provisional three-dimensional extracellular matrix or scaffold to establish a fiber structure. Therefore, the resulting tissue structure and mechanical characteristics were determined solely by the cells. Due to the self-assembly nature of this approach, the growing fibers exhibit some key aspects of embryonic tendon development, such as high cellularity, the rapid formation (within 24 h) of a highly organized and aligned cellular structure, and the expression of cadherin-11 (indicating direct cell-to-cell adhesions). To provide a dynamic mechanical environment, we have also developed and characterized a method to apply precise cyclic tensile strain to the cellular fibers as they develop. After an initial period of cellular fiber formation (24 h postseeding), cyclic strain was applied for 48 h, in 8-h intervals, with tensile strain increasing from 0.7% to 1.0%, and at a frequency of 0.5 Hz. Dynamic loading dramatically increased cellular fiber mechanical properties with a nearly twofold increase in both the linear region stiffness and maximum load at failure, thereby demonstrating a mechanism for enhancing cellular fiber formation and mechanical properties. Tissue engineering strategies, designed to capture key aspects of embryonic development, may provide unique insight into accelerated maturation of engineered replacement tissue, and offer significant advances for regenerative medicine applications in tendon, ligament, and other fibrous soft tissues.

Dynamic Mechanical Compression of Chondrocytes for Tissue Engineering: A Critical Review.

PubMed

Anderson, Devon E; Johnstone, Brian

2017-01-01

Articular cartilage functions to transmit and translate loads. In a classical structure-function relationship, the tissue resides in a dynamic mechanical environment that drives the formation of a highly organized tissue architecture suited to its biomechanical role. The dynamic mechanical environment includes multiaxial compressive and shear strains as well as hydrostatic and osmotic pressures. As the mechanical environment is known to modulate cell fate and influence tissue development toward a defined architecture in situ , dynamic mechanical loading has been hypothesized to induce the structure-function relationship during attempts at in vitro regeneration of articular cartilage. Researchers have designed increasingly sophisticated bioreactors with dynamic mechanical regimes, but the response of chondrocytes to dynamic compression and shear loading remains poorly characterized due to wide variation in study design, system variables, and outcome measurements. We assessed the literature pertaining to the use of dynamic compressive bioreactors for in vitro generation of cartilaginous tissue from primary and expanded chondrocytes. We used specific search terms to identify relevant publications from the PubMed database and manually sorted the data. It was very challenging to find consensus between studies because of species, age, cell source, and culture differences, coupled with the many loading regimes and the types of analyses used. Early studies that evaluated the response of primary bovine chondrocytes within hydrogels, and that employed dynamic single-axis compression with physiologic loading parameters, reported consistently favorable responses at the tissue level, with upregulation of biochemical synthesis and biomechanical properties. However, they rarely assessed the cellular response with gene expression or mechanotransduction pathway analyses. Later studies that employed increasingly sophisticated biomaterial-based systems, cells derived from different species, and complex loading regimes, did not necessarily corroborate prior positive results. These studies report positive results with respect to very specific conditions for cellular responses to dynamic load but fail to consistently achieve significant positive changes in relevant tissue engineering parameters, particularly collagen content and stiffness. There is a need for standardized methods and analyses of dynamic mechanical loading systems to guide the field of tissue engineering toward building cartilaginous implants that meet the goal of regenerating articular cartilage.

Phenomenology based multiscale models as tools to understand cell membrane and organelle morphologies

PubMed Central

Ramakrishnan, N.; Radhakrishnan, Ravi

2016-01-01

An intriguing question in cell biology is “how do cells regulate their shape?” It is commonly believed that the observed cellular morphologies are a result of the complex interaction among the lipid molecules (constituting the cell membrane), and with a number of other macromolecules, such as proteins. It is also believed that the common biophysical processes essential for the functioning of a cell also play an important role in cellular morphogenesis. At the cellular scale—where typical dimensions are in the order of micrometers—the effects arising from the molecular scale can either be modeled as equilibrium or non-equilibrium processes. In this chapter, we discuss the dynamically triangulated Monte Carlo technique to model and simulate membrane morphologies at the cellular scale, which in turn can be used to investigate several questions related to shape regulation in cells. In particular, we focus on two specific problems within the framework of isotropic and anisotropic elasticity theories: namely, (i) the origin of complex, physiologically relevant, membrane shapes due to the interaction of the membrane with curvature remodeling proteins, and (ii) the genesis of steady state cellular shapes due to the action of non-equilibrium forces that are generated by the fission and fusion of transport vesicles and by the binding and unbinding of proteins from the parent membrane. PMID:27087801

Fluorescence-encoded gold nanoparticles: library design and modulation of cellular uptake into dendritic cells.

PubMed

Rodriguez-Lorenzo, Laura; Fytianos, Kleanthis; Blank, Fabian; von Garnier, Christophe; Rothen-Rutishauser, Barbara; Petri-Fink, Alke

2014-04-09

In order to harness the unique properties of nanoparticles for novel clinical applications and to modulate their uptake into specific immune cells we designed a new library of homo- and hetero-functional fluorescence-encoded gold nanoparticles (Au-NPs) using different poly(vinyl alcohol) and poly(ethylene glycol)-based polymers for particle coating and stabilization. The encoded particles were fully characterized by UV-Vis and fluorescence spectroscopy, zeta potential and dynamic light scattering. The uptake by human monocyte derived dendritic cells in vitro was studied by confocal laser scanning microscopy and quantified by fluorescence-activated cell sorting and inductively coupled plasma atomic emission spectroscopy. We show how the chemical modification of particle surfaces, for instance by attaching fluorescent dyes, can conceal fundamental particle properties and modulate cellular uptake. In order to mask the influence of fluorescent dyes on cellular uptake while still exploiting its fluorescence for detection, we have created hetero-functionalized Au-NPs, which again show typical particle dependent cellular interactions. Our study clearly prove that the thorough characterization of nanoparticles at each modification step in the engineering process is absolutely essential and that it can be necessary to make substantial adjustments of the particles in order to obtain reliable cellular uptake data, which truly reflects particle properties. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of Actin-Based Intracellular Trafficking in Pollen Tubes.

PubMed

Jiang, Yuxiang; Zhang, Meng; Huang, Shanjin

2017-01-01

Underlying rapid and directional pollen tube growth is the active intracellular trafficking system that carries materials necessary for cell wall synthesis and membrane expansion to the expanding point of the pollen tube. The actin cytoskeleton has been shown to control various intracellular trafficking events in the pollen tube, but the underlying cellular and molecular mechanisms remain poorly understood. To better understand how the actin cytoskeleton is involved in the regulation of intracellular trafficking events, we need to establish assays to visualize and quantify the distribution and dynamics of organelles, vesicles, or secreted proteins. In this chapter, we introduce methods regarding the visualization and quantification of the distribution and dynamics of organelles or vesicles in pollen tubes.

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks

PubMed Central

Rich, Scott; Booth, Victoria; Zochowski, Michal

2016-01-01

The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics compared to those in networks of Type I or Type II neurons. To understand these results, we compute neuronal PRCs calculated with a perturbation matching the profile of the synaptic current in our networks. Differences in profiles of these PRCs across the different neuron types reveal mechanisms underlying the divergent network dynamics. PMID:27812323

Modifications in small nuclear RNAs and their roles in spliceosome assembly and function.

PubMed

Bohnsack, Markus T; Sloan, Katherine E

2018-06-01

Modifications in cellular RNAs have emerged as key regulators of all aspects of gene expression, including pre-mRNA splicing. During spliceosome assembly and function, the small nuclear RNAs (snRNAs) form numerous dynamic RNA-RNA and RNA-protein interactions, which are required for spliceosome assembly, correct positioning of the spliceosome on substrate pre-mRNAs and catalysis. The human snRNAs contain several base methylations as well as a myriad of pseudouridines and 2'-O-methylated nucleotides, which are largely introduced by small Cajal body-specific-RNPs. Modified nucleotides typically cluster in functionally important regions of the snRNAs, suggesting that their presence could optimise the interactions of snRNAs with each other or with pre-mRNAs, or may affect the binding of spliceosomal proteins. snRNA modifications appear to play important roles in snRNP biogenesis and spliceosome assembly, and have also been proposed to influence the efficiency and fidelity of pre-mRNAs splicing. Interestingly, alterations in the modification status of snRNAs have recently been observed in different cellular conditions, implying that some snRNA modifications are dynamic and raising the possibility that these modifications may fine-tune the spliceosome for particular functions. Here, we review the current knowledge on the snRNA modification machinery and discuss the timing, functions and dynamics of modifications in snRNAs.

Animal cell hydraulics.

PubMed

Charras, Guillaume T; Mitchison, Timothy J; Mahadevan, L

2009-09-15

Water is the dominant ingredient of cells and its dynamics are crucial to life. We and others have suggested a physical picture of the cell as a soft, fluid-infiltrated sponge, surrounded by a water-permeable barrier. To understand water movements in an animal cell, we imposed an external, inhomogeneous osmotic stress on cultured cancer cells. This forced water through the membrane on one side, and out on the other. Inside the cell, it created a gradient in hydration, that we visualized by tracking cellular responses using natural organelles and artificially introduced quantum dots. The dynamics of these markers at short times were the same for normal and metabolically poisoned cells, indicating that the cellular responses are primarily physical rather than chemical. Our finding of an internal gradient in hydration is inconsistent with a continuum model for cytoplasm, but consistent with the sponge model, and implies that the effective pore size of the sponge is small enough to retard water flow significantly on time scales ( approximately 10-100 seconds) relevant to cell physiology. We interpret these data in terms of a theoretical framework that combines mechanics and hydraulics in a multiphase poroelastic description of the cytoplasm and explains the experimentally observed dynamics quantitatively in terms of a few coarse-grained parameters that are based on microscopically measurable structural, hydraulic and mechanical properties. Our fluid-filled sponge model could provide a unified framework to understand a number of disparate observations in cell morphology and motility.

Fluorescent Reporters and Biosensors for Probing the Dynamic Behavior of Protein Kinases

PubMed Central

González-Vera, Juan A.; Morris, May C.

2015-01-01

Probing the dynamic activities of protein kinases in real-time in living cells constitutes a major challenge that requires specific and sensitive tools tailored to meet the particular demands associated with cellular imaging. The development of genetically-encoded and synthetic fluorescent biosensors has provided means of monitoring protein kinase activities in a non-invasive fashion in their native cellular environment with high spatial and temporal resolution. Here, we review existing technologies to probe different dynamic features of protein kinases and discuss limitations where new developments are required to implement more performant tools, in particular with respect to infrared and near-infrared fluorescent probes and strategies which enable improved signal-to-noise ratio and controlled activation of probes. PMID:28248276

Mechanical characterization of disordered and anisotropic cellular monolayers

NASA Astrophysics Data System (ADS)

Nestor-Bergmann, Alexander; Johns, Emma; Woolner, Sarah; Jensen, Oliver E.

2018-05-01

We consider a cellular monolayer, described using a vertex-based model, for which cells form a spatially disordered array of convex polygons that tile the plane. Equilibrium cell configurations are assumed to minimize a global energy defined in terms of cell areas and perimeters; energy is dissipated via dynamic area and length changes, as well as cell neighbor exchanges. The model captures our observations of an epithelium from a Xenopus embryo showing that uniaxial stretching induces spatial ordering, with cells under net tension (compression) tending to align with (against) the direction of stretch, but with the stress remaining heterogeneous at the single-cell level. We use the vertex model to derive the linearized relation between tissue-level stress, strain, and strain rate about a deformed base state, which can be used to characterize the tissue's anisotropic mechanical properties; expressions for viscoelastic tissue moduli are given as direct sums over cells. When the base state is isotropic, the model predicts that tissue properties can be tuned to a regime with high elastic shear resistance but low resistance to area changes, or vice versa.

Orthogonal Operation of Constitutional Dynamic Networks Consisting of DNA-Tweezer Machines.

PubMed

Yue, Liang; Wang, Shan; Cecconello, Alessandro; Lehn, Jean-Marie; Willner, Itamar

2017-12-26

Overexpression or down-regulation of cellular processes are often controlled by dynamic chemical networks. Bioinspired by nature, we introduce constitutional dynamic networks (CDNs) as systems that emulate the principle of the nature processes. The CDNs comprise dynamically interconvertible equilibrated constituents that respond to external triggers by adapting the composition of the dynamic mixture to the energetic stabilization of the constituents. We introduce a nucleic acid-based CDN that includes four interconvertible and mechanically triggered tweezers, AA', BB', AB' and BA', existing in closed, closed, open, and open configurations, respectively. By subjecting the CDN to auxiliary triggers, the guided stabilization of one of the network constituents dictates the dynamic reconfiguration of the structures of the tweezers constituents. The orthogonal and reversible operations of the CDN DNA tweezers are demonstrated, using T-A·T triplex or K + -stabilized G-quadruplex as structural motifs that control the stabilities of the constituents. The implications of the study rest on the possible applications of input-guided CDN assemblies for sensing, logic gate operations, and programmed activation of molecular machines.

Identification of infection- and defense-related genes via a dynamic host-pathogen interaction network using a Candida albicans-zebrafish infection model.

PubMed

Kuo, Zong-Yu; Chuang, Yung-Jen; Chao, Chun-Cheih; Liu, Fu-Chen; Lan, Chung-Yu; Chen, Bor-Sen

2013-01-01

Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs. Copyright © 2013 S. Karger AG, Basel.

Quantitative and Dynamic Imaging of ATM Kinase Activity by Bioluminescence Imaging.

PubMed

Nyati, Shyam; Young, Grant; Ross, Brian Dale; Rehemtulla, Alnawaz

2017-01-01

Ataxia telangiectasia mutated (ATM) is a serine/threonine kinase critical to the cellular DNA damage response, including DNA double strand breaks (DSBs). ATM activation results in the initiation of a complex cascade of events facilitating DNA damage repair, cell cycle checkpoint control, and survival. Traditionally, protein kinases have been analyzed in vitro using biochemical methods (kinase assays using purified proteins or immunological assays) requiring a large number of cells and cell lysis. Genetically encoded biosensors based on optical molecular imaging such as fluorescence or bioluminescence have been developed to enable interrogation of kinase activities in live cells with a high signal to background. We have genetically engineered a hybrid protein whose bioluminescent activity is dependent on the ATM-mediated phosphorylation of a substrate. The engineered protein consists of the split luciferase-based protein complementation pair with a CHK2 (a substrate for ATM kinase activity) target sequence and a phospho-serine/threonine-binding domain, FHA2, derived from yeast Rad53. Phosphorylation of the serine residue within the target sequence by ATM would lead to its interaction with the phospho-serine-binding domain, thereby preventing complementation of the split luciferase pair and loss of reporter activity. Bioluminescence imaging of reporter-expressing cells in cultured plates or as mouse xenografts provides a quantitative surrogate for ATM kinase activity and therefore the cellular DNA damage response in a noninvasive, dynamic fashion.

Quantitative and Dynamic Imaging of ATM Kinase Activity.

PubMed

Nyati, Shyam; Young, Grant; Ross, Brian Dale; Rehemtulla, Alnawaz

2017-01-01

Ataxia telangiectasia mutated (ATM) is a serine/threonine kinase critical to the cellular DNA-damage response, including DNA double-strand breaks (DSBs). ATM activation results in the initiation of a complex cascade of events facilitating DNA damage repair, cell cycle checkpoint control, and survival. Traditionally, protein kinases have been analyzed in vitro using biochemical methods (kinase assays using purified proteins or immunological assays) requiring a large number of cells and cell lysis. Genetically encoded biosensors based on optical molecular imaging such as fluorescence or bioluminescence have been developed to enable interrogation of kinase activities in live cells with a high signal to background. We have genetically engineered a hybrid protein whose bioluminescent activity is dependent on the ATM-mediated phosphorylation of a substrate. The engineered protein consists of the split luciferase-based protein complementation pair with a CHK2 (a substrate for ATM kinase activity) target sequence and a phospho-serine/threonine-binding domain, FHA2, derived from yeast Rad53. Phosphorylation of the serine residue within the target sequence by ATM would lead to its interaction with the phospho-serine-binding domain, thereby preventing complementation of the split luciferase pair and loss of reporter activity. Bioluminescence imaging of reporter expressing cells in cultured plates or as mouse xenografts provides a quantitative surrogate for ATM kinase activity and therefore the cellular DNA damage response in a noninvasive, dynamic fashion.

Imaging Cellular Dynamics with Spectral Relaxation Imaging Microscopy: Distinct Spectral Dynamics in Golgi Membranes of Living Cells.

PubMed

Lajevardipour, Alireza; Chon, James W M; Chattopadhyay, Amitabha; Clayton, Andrew H A

2016-11-22

Spectral relaxation from fluorescent probes is a useful technique for determining the dynamics of condensed phases. To this end, we have developed a method based on wide-field spectral fluorescence lifetime imaging microscopy to extract spectral relaxation correlation times of fluorescent probes in living cells. We show that measurement of the phase and modulation of fluorescence from two wavelengths permit the identification and determination of excited state lifetimes and spectral relaxation correlation times at a single modulation frequency. For NBD fluorescence in glycerol/water mixtures, the spectral relaxation correlation time determined by our approach exhibited good agreement with published dielectric relaxation measurements. We applied this method to determine the spectral relaxation dynamics in membranes of living cells. Measurements of the Golgi-specific C 6 -NBD-ceramide probe in living HeLa cells revealed sub-nanosecond spectral dynamics in the intracellular Golgi membrane and slower nanosecond spectral dynamics in the extracellular plasma membrane. We interpret the distinct spectral dynamics as a result of structural plasticity of the Golgi membrane relative to more rigid plasma membranes. To the best of our knowledge, these results constitute one of the first measurements of Golgi rotational dynamics.

In vitro stimulation of vascular endothelial growth factor by borate-based glass fibers under dynamic flow conditions.

PubMed

Chen, Sisi; Yang, Qingbo; Brow, Richard K; Liu, Kun; Brow, Katherine A; Ma, Yinfa; Shi, Honglan

2017-04-01

Bioactive borate glass has been recognized to have both hard and soft tissue repair and regeneration capabilities through stimulating both osteogenesis and angiogenesis. However, the underlying biochemical and cellular mechanisms remain unclear. In this study, dynamic flow culturing modules were designed to simulate the micro-environment near the vascular depletion and hyperplasia area in wound-healing regions, thus to better investigate the mechanisms underlying the biocompatibility and functionality of borate-based glass materials. Glass fibers were dosed either upstream or in contact with the pre-seeded cells in the dynamic flow module. Two types of borate glasses, doped with (1605) or without (13-93B3) CuO and ZnO, were studied along with the silicate-based glass, 45S5. Substantial fiber dissolution in cell culture medium was observed, leading to the release of ions (boron, sodium and potassium) and the deposition of a calcium phosphate phase. Different levels of vascular endothelial growth factor secretion were observed from cells exposed to these three glass fibers, and the copper/zinc containing borate 1605 fibers exhibited the most positive influence. These results indicate that dynamic studies of in vitro bioactivity provide useful information to understand the in vivo response to bioactive borate glasses. Copyright © 2016 Elsevier B.V. All rights reserved.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

A methodological approach for using high-level Petri Nets to model the immune system response.

PubMed

Pennisi, Marzio; Cavalieri, Salvatore; Motta, Santo; Pappalardo, Francesco

2016-12-22

Mathematical and computational models showed to be a very important support tool for the comprehension of the immune system response against pathogens. Models and simulations allowed to study the immune system behavior, to test biological hypotheses about diseases and infection dynamics, and to improve and optimize novel and existing drugs and vaccines. Continuous models, mainly based on differential equations, usually allow to qualitatively study the system but lack in description; conversely discrete models, such as agent based models and cellular automata, permit to describe in detail entities properties at the cost of losing most qualitative analyses. Petri Nets (PN) are a graphical modeling tool developed to model concurrency and synchronization in distributed systems. Their use has become increasingly marked also thanks to the introduction in the years of many features and extensions which lead to the born of "high level" PN. We propose a novel methodological approach that is based on high level PN, and in particular on Colored Petri Nets (CPN), that can be used to model the immune system response at the cellular scale. To demonstrate the potentiality of the approach we provide a simple model of the humoral immune system response that is able of reproducing some of the most complex well-known features of the adaptive response like memory and specificity features. The methodology we present has advantages of both the two classical approaches based on continuous and discrete models, since it allows to gain good level of granularity in the description of cells behavior without losing the possibility of having a qualitative analysis. Furthermore, the presented methodology based on CPN allows the adoption of the same graphical modeling technique well known to life scientists that use PN for the modeling of signaling pathways. Finally, such an approach may open the floodgates to the realization of multi scale models that integrate both signaling pathways (intra cellular) models and cellular (population) models built upon the same technique and software.

Dynamics of cell shape and forces on micropatterned substrates predicted by a cellular Potts model.

PubMed

Albert, Philipp J; Schwarz, Ulrich S

2014-06-03

Micropatterned substrates are often used to standardize cell experiments and to quantitatively study the relation between cell shape and function. Moreover, they are increasingly used in combination with traction force microscopy on soft elastic substrates. To predict the dynamics and steady states of cell shape and forces without any a priori knowledge of how the cell will spread on a given micropattern, here we extend earlier formulations of the two-dimensional cellular Potts model. The third dimension is treated as an area reservoir for spreading. To account for local contour reinforcement by peripheral bundles, we augment the cellular Potts model by elements of the tension-elasticity model. We first parameterize our model and show that it accounts for momentum conservation. We then demonstrate that it is in good agreement with experimental data for shape, spreading dynamics, and traction force patterns of cells on micropatterned substrates. We finally predict shapes and forces for micropatterns that have not yet been experimentally studied. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Dynamic cellular manufacturing system considering machine failure and workload balance

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

Dynamic NF-κB and E2F interactions control the priority and timing of inflammatory signalling and cell proliferation

PubMed Central

Ankers, John M; Awais, Raheela; Jones, Nicholas A; Boyd, James; Ryan, Sheila; Adamson, Antony D; Harper, Claire V; Bridge, Lloyd; Spiller, David G; Jackson, Dean A; Paszek, Pawel; Sée, Violaine; White, Michael RH

2016-01-01

Dynamic cellular systems reprogram gene expression to ensure appropriate cellular fate responses to specific extracellular cues. Here we demonstrate that the dynamics of Nuclear Factor kappa B (NF-κB) signalling and the cell cycle are prioritised differently depending on the timing of an inflammatory signal. Using iterative experimental and computational analyses, we show physical and functional interactions between NF-κB and the E2 Factor 1 (E2F-1) and E2 Factor 4 (E2F-4) cell cycle regulators. These interactions modulate the NF-κB response. In S-phase, the NF-κB response was delayed or repressed, while cell cycle progression was unimpeded. By contrast, activation of NF-κB at the G1/S boundary resulted in a longer cell cycle and more synchronous initial NF-κB responses between cells. These data identify new mechanisms by which the cellular response to stress is differentially controlled at different stages of the cell cycle. DOI: http://dx.doi.org/10.7554/eLife.10473.001 PMID:27185527

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

Research highlights: microfluidics meets big data.

PubMed

Tseng, Peter; Weaver, Westbrook M; Masaeli, Mahdokht; Owsley, Keegan; Di Carlo, Dino

2014-03-07

In this issue we highlight a collection of recent work in which microfluidic parallelization and automation have been employed to address the increasing need for large amounts of quantitative data concerning cellular function--from correlating microRNA levels to protein expression, increasing the throughput and reducing the noise when studying protein dynamics in single-cells, and understanding how signal dynamics encodes information. The painstaking dissection of cellular pathways one protein at a time appears to be coming to an end, leading to more rapid discoveries which will inevitably translate to better cellular control--in producing useful gene products and treating disease at the individual cell level. From these studies it is also clear that development of large scale mutant or fusion libraries, automation of microscopy, image analysis, and data extraction will be key components as microfluidics contributes its strengths to aid systems biology moving forward.

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions.

PubMed

Saha, Tanumoy; Rathmann, Isabel; Galic, Milos

2017-07-11

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

Multiplexed Imaging of Protein Phosphorylation on Membranes Based on Ti(IV) Functionalized Nanopolymers.

PubMed

Iliuk, Anton; Li, Li; Melesse, Michael; Hall, Mark C; Tao, W Andy

2016-05-17

Accurate protein phosphorylation analysis reveals dynamic cellular signaling events not evident from protein expression levels. The most dominant biochemical assay, western blotting, suffers from the inadequate availability and poor quality of phospho-specific antibodies for phosphorylated proteins. Furthermore, multiplexed assays based on antibodies are limited by steric interference between the antibodies. Here we introduce a multifunctionalized nanopolymer for the universal detection of phosphoproteins that, in combination with regular antibodies, allows multiplexed imaging and accurate determination of protein phosphorylation on membranes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

NASA Astrophysics Data System (ADS)

Tian, Li-Jun; Huang, Hai-Jun; Liu, Tian-Liang

2009-07-01

We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers' route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers' travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

Molecular modeling of the conformational dynamics of the cellular prion protein

NASA Astrophysics Data System (ADS)

Nguyen, Charles; Colling, Ian; Bartz, Jason; Soto, Patricia

2014-03-01

Prions are infectious agents responsible for transmissible spongiform encephalopathies (TSEs), a type of fatal neurodegenerative disease in mammals. Prions propagate biological information by conversion of the non-pathological version of the prion protein to the infectious conformation, PrPSc. A wealth of knowledge has shed light on the nature and mechanism of prion protein conversion. In spite of the significance of this problem, we are far from fully understanding the conformational dynamics of the cellular isoform. To remedy this situation we employ multiple biomolecular modeling techniques such as docking and molecular dynamics simulations to map the free energy landscape and determine what specific regions of the prion protein are most conductive to binding. The overall goal is to characterize the conformational dynamics of the cell form of the prion protein, PrPc, to gain insight into inhibition pathways against misfolding. NE EPSCoR FIRST Award to Patricia Soto.

Dynamin-Related Protein 1 and Mitochondrial Fragmentation in Neurodegenerative Diseases

PubMed Central

Reddy, P. Hemachandra; Reddy, Tejaswini P.; Manczak, Maria; Calkins, Marcus J.; Shirendeb, Ulziibat; Mao, Peizhong

2010-01-01

The purpose of this article is to review the recent developments of abnormal mitochondrial dynamics, mitochondrial fragmentation, and neuronal damage in neurodegenerative diseases, including Alzheimer’s, Parkinson’s, Huntington’s, and amyotrophic lateral sclerosis. The GTPase family of proteins, including fission proteins, dynamin related protein 1 (Drp1), mitochondrial fission 1 (Fis1), and fusion proteins (Mfn1, Mfn2 and Opa1) are essential to maintain mitochondrial fission and fusion balance, and to provide necessary adenosine triphosphate to neurons. Among these, Drp1 is involved in several important aspects of mitochondria, including shape, size, distribution, remodeling, and maintenance of X in mammalian cells. In addition, recent advancements in molecular, cellular, electron microscopy, and confocal imaging studies revealed that Drp1 is associated with several cellular functions, including mitochondrial and peroxisomal fragmentation, phosphorylation, SUMOylation, ubiquitination, and cell death. In the last two decades, tremendous progress has been made in researching mitochondrial dynamics, in yeast, worms, and mammalian cells; and this research has provided evidence linking Drp1 to neurodegenerative diseases. Researchers in the neurodegenerative disease field are beginning to recognize the possible involvement of Drp1 in causing mitochondrial fragmentation and abnormal mitochondrial dynamics in neurodegenerative diseases. This article summarizes research findings relating Drp1 to mitochondrial fission and fusion, in yeast, worms, and mammals. Based on findings from the Reddy laboratory and others’, we propose that mutant proteins of neurodegenerative diseases, including AD, PD, HD, and ALS, interact with Drp1, activate mitochondrial fission machinery, fragment mitochondria excessively, and impair mitochondrial transport and mitochondrial dynamics, ultimately causing mitochondrial dysfunction and neuronal damage. PMID:21145355

Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential

PubMed Central

Kaneko, Kunihiko

2011-01-01

The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems. PMID:22073296

Diversity in times of adversity: probabilistic strategies in microbial survival games.

PubMed

Wolf, Denise M; Vazirani, Vijay V; Arkin, Adam P

2005-05-21

Population diversification strategies are ubiquitous among microbes, encompassing random phase-variation (RPV) of pathogenic bacteria, viral latency as observed in some bacteriophage and HIV, and the non-genetic diversity of bacterial stress responses. Precise conditions under which these diversification strategies confer an advantage have not been well defined. We develop a model of population growth conditioned on dynamical environmental and cellular states. Transitions among cellular states, in turn, may be biased by possibly noisy readings of the environment from cellular sensors. For various types of environmental dynamics and cellular sensor capability, we apply game-theoretic analysis to derive the evolutionarily stable strategy (ESS) for an organism and determine when that strategy is diversification. We find that: (1) RPV, effecting a sort of Parrondo paradox wherein random alternations between losing strategies produce a winning strategy, is selected when transitions between different selective environments cannot be sensed, (2) optimal RPV cell switching rates are a function of environmental lifecycle asymmetries and environmental autocorrelation, (3) probabilistic diversification upon entering a new environment is selected when sensors can detect environmental transitions but have poor precision in identifying new environments, and (4) in the presence of excess additive noise, low-pass filtering is required for evolutionary stability. We show that even when RPV is not the ESS, it may minimize growth rate variance and the risk of extinction due to 'unlucky' environmental dynamics.

Literature Review on Dynamic Cellular Manufacturing System

NASA Astrophysics Data System (ADS)

Nouri Houshyar, A.; Leman, Z.; Pakzad Moghadam, H.; Ariffin, M. K. A. M.; Ismail, N.; Iranmanesh, H.

2014-06-01

In previous decades, manufacturers faced a lot of challenges because of globalization and high competition in markets. These problems arise from shortening product life cycle, rapid variation in demand of products, and also rapid changes in manufcaturing technologies. Nowadays most manufacturing companies expend considerable attention for improving flexibility and responsiveness in order to overcome these kinds of problems and also meet customer's needs. By considering the trend toward the shorter product life cycle, the manufacturing environment is towards manufacturing a wide variety of parts in small batches [1]. One of the major techniques which are applied for improving manufacturing competitiveness is Cellular Manufacturing System (CMS). CMS is type of manufacturing system which tries to combine flexibility of job shop and also productivity of flow shop. In addition, Dynamic cellular manufacturing system which considers different time periods for the manufacturing system becomes an important topic and attracts a lot of attention to itself. Therefore, this paper made attempt to have a brief review on this issue and focused on all published paper on this subject. Although, this topic gains a lot of attention to itself during these years, none of previous researchers focused on reviewing the literature of that which can be helpful and useful for other researchers who intend to do the research on this topic. Therefore, this paper is the first study which has focused and reviewed the literature of dynamic cellular manufacturing system.

Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic 'two component system' protein network.

PubMed

Di Paola, Vieri; Marijuán, Pedro C; Lahoz-Beltra, Rafael

2004-01-01

Adaptive behavior in unicellular organisms (i.e., bacteria) depends on highly organized networks of proteins governing purposefully the myriad of molecular processes occurring within the cellular system. For instance, bacteria are able to explore the environment within which they develop by utilizing the motility of their flagellar system as well as a sophisticated biochemical navigation system that samples the environmental conditions surrounding the cell, searching for nutrients or moving away from toxic substances or dangerous physical conditions. In this paper we discuss how proteins of the intervening signal transduction network could be modeled as artificial neurons, simulating the dynamical aspects of the bacterial taxis. The model is based on the assumption that, in some important aspects, proteins can be considered as processing elements or McCulloch-Pitts artificial neurons that transfer and process information from the bacterium's membrane surface to the flagellar motor. This simulation of bacterial taxis has been carried out on a hardware realization of a McCulloch-Pitts artificial neuron using an operational amplifier. Based on the behavior of the operational amplifier we produce a model of the interaction between CheY and FliM, elements of the prokaryotic two component system controlling chemotaxis, as well as a simulation of learning and evolution processes in bacterial taxis. On the one side, our simulation results indicate that, computationally, these protein 'switches' are similar to McCulloch-Pitts artificial neurons, suggesting a bridge between evolution and learning in dynamical systems at cellular and molecular levels and the evolutive hardware approach. On the other side, important protein 'tactilizing' properties are not tapped by the model, and this suggests further complexity steps to explore in the approach to biological molecular computing.

Spatiotemporal dynamics of DNA repair proteins following laser microbeam induced DNA damage – When is a DSB not a DSB?☆

PubMed Central

Reynolds, Pamela; Botchway, Stanley W.; Parker, Anthony W.; O’Neill, Peter

2013-01-01

The formation of DNA lesions poses a constant threat to cellular stability. Repair of endogenously and exogenously produced lesions has therefore been extensively studied, although the spatiotemporal dynamics of the repair processes has yet to be fully understood. One of the most recent advances to study the kinetics of DNA repair has been the development of laser microbeams to induce and visualize recruitment and loss of repair proteins to base damage in live mammalian cells. However, a number of studies have produced contradictory results that are likely caused by the different laser systems used reflecting in part the wavelength dependence of the damage induced. Additionally, the repair kinetics of laser microbeam induced DNA lesions have generally lacked consideration of the structural and chemical complexity of the DNA damage sites, which are known to greatly influence their reparability. In this review, we highlight the key considerations when embarking on laser microbeam experiments and interpreting the real time data from laser microbeam irradiations. We compare the repair kinetics from live cell imaging with biochemical and direct quantitative cellular measurements for DNA repair. PMID:23688615

Network and intrinsic cellular mechanisms underlying theta phase precession of hippocampal neurons.

PubMed

Maurer, Andrew P; McNaughton, Bruce L

2007-07-01

Hippocampal 'place cells' systematically shift their phase of firing in relation to the theta rhythm as an animal traverses the 'place field'. These dynamics imply that the neural ensemble begins each theta cycle at a point in its state-space that might 'represent' the current location of the rat, but that the ensemble 'looks ahead' during the rest of the cycle. Phase precession could result from intrinsic cellular dynamics involving interference of two oscillators of different frequencies, or from network interactions, similar to Hebb's 'phase sequence' concept, involving asymmetric synaptic connections. Both models have difficulties accounting for all of the available experimental data, however. A hybrid model, in which the look-ahead phenomenon implied by phase precession originates in superficial entorhinal cortex by some form of interference mechanism and is enhanced in the hippocampus proper by asymmetric synaptic plasticity during sequence encoding, seems to be consistent with available data, but as yet there is no fully satisfactory theoretical account of this phenomenon. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

Transition of dislocation glide to shear transformation in shocked tantalum

DOE PAGES

Hsiung, Luke L.; Campbell, Geoffrey H.

2017-02-28

A TEM study of pure tantalum and tantalum-tungsten alloys explosively shocked at a peak pressure of 30 GPa (strain rate: ~1 x 10 4 sec -1) is presented. While no ω (hexagonal) phase was found in shock-recovered pure Ta and Ta-5W that contain mainly a low-energy cellular dislocation structure, shock-induced ω phase was found to form in Ta-10W that contains evenly distributed dislocations with a stored dislocation density higher than 1 x 10 12 cm -2. The TEM results clearly reveal that shock-induced α (bcc) → ω (hexagonal) shear transformation occurs when dynamic recovery reactions which lead the formation low-energymore » cellular dislocation structure become largely suppressed in Ta-10W shocked under dynamic (i.e., high strain-rate and high-pressure) conditions. A novel dislocation-based mechanism is proposed to rationalize the transition of dislocation glide to twinning and/or shear transformation in shock-deformed tantalum. Lastly, twinning and/or shear transformation take place as an alternative deformation mechanism to accommodate high-strain-rate straining when the shear stress required for dislocation multiplication exceeds the threshold shear stresses for twinning and/or shear transformation.« less

Spatiotemporal dynamics of oscillatory cellular patterns in three-dimensional directional solidification.

PubMed

Bergeon, N; Tourret, D; Chen, L; Debierre, J-M; Guérin, R; Ramirez, A; Billia, B; Karma, A; Trivedi, R

2013-05-31

We report results of directional solidification experiments conducted on board the International Space Station and quantitative phase-field modeling of those experiments. The experiments image for the first time in situ the spatially extended dynamics of three-dimensional cellular array patterns formed under microgravity conditions where fluid flow is suppressed. Experiments and phase-field simulations reveal the existence of oscillatory breathing modes with time periods of several 10's of minutes. Oscillating cells are usually noncoherent due to array disorder, with the exception of small areas where the array structure is regular and stable.

Inference for dynamics of continuous variables: the extended Plefka expansion with hidden nodes

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.

2017-06-01

We consider the problem of a subnetwork of observed nodes embedded into a larger bulk of unknown (i.e. hidden) nodes, where the aim is to infer these hidden states given information about the subnetwork dynamics. The biochemical networks underlying many cellular and metabolic processes are important realizations of such a scenario as typically one is interested in reconstructing the time evolution of unobserved chemical concentrations starting from the experimentally more accessible ones. We present an application to this problem of a novel dynamical mean field approximation, the extended Plefka expansion, which is based on a path integral description of the stochastic dynamics. As a paradigmatic model we study the stochastic linear dynamics of continuous degrees of freedom interacting via random Gaussian couplings. The resulting joint distribution is known to be Gaussian and this allows us to fully characterize the posterior statistics of the hidden nodes. In particular the equal-time hidden-to-hidden variance—conditioned on observations—gives the expected error at each node when the hidden time courses are predicted based on the observations. We assess the accuracy of the extended Plefka expansion in predicting these single node variances as well as error correlations over time, focussing on the role of the system size and the number of observed nodes.

A novel grid-based mesoscopic model for evacuation dynamics

NASA Astrophysics Data System (ADS)

Shi, Meng; Lee, Eric Wai Ming; Ma, Yi

2018-05-01

This study presents a novel grid-based mesoscopic model for evacuation dynamics. In this model, the evacuation space is discretised into larger cells than those used in microscopic models. This approach directly computes the dynamic changes crowd densities in cells over the course of an evacuation. The density flow is driven by the density-speed correlation. The computation is faster than in traditional cellular automata evacuation models which determine density by computing the movements of each pedestrian. To demonstrate the feasibility of this model, we apply it to a series of practical scenarios and conduct a parameter sensitivity study of the effect of changes in time step δ. The simulation results show that within the valid range of δ, changing δ has only a minor impact on the simulation. The model also makes it possible to directly acquire key information such as bottleneck areas from a time-varied dynamic density map, even when a relatively large time step is adopted. We use the commercial software AnyLogic to evaluate the model. The result shows that the mesoscopic model is more efficient than the microscopic model and provides more in-situ details (e.g., pedestrian movement pattern) than the macroscopic models.

Simultaneous quantification of actin monomer and filament dynamics with modeling-assisted analysis of photoactivation

PubMed Central

Kapustina, Maryna; Read, Tracy-Ann

2016-01-01

ABSTRACT Photoactivation allows one to pulse-label molecules and obtain quantitative data about their behavior. We have devised a new modeling-based analysis for photoactivatable actin experiments that simultaneously measures properties of monomeric and filamentous actin in a three-dimensional cellular environment. We use this method to determine differences in the dynamic behavior of β- and γ-actin isoforms, showing that both inhabit filaments that depolymerize at equal rates but that β-actin exists in a higher monomer-to-filament ratio. We also demonstrate that cofilin (cofilin 1) equally accelerates depolymerization of filaments made from both isoforms, but is only required to maintain the β-actin monomer pool. Finally, we used modeling-based analysis to assess actin dynamics in axon-like projections of differentiating neuroblastoma cells, showing that the actin monomer concentration is significantly depleted as the axon develops. Importantly, these results would not have been obtained using traditional half-time analysis. Given that parameters of the publicly available modeling platform can be adjusted to suit the experimental system of the user, this method can easily be used to quantify actin dynamics in many different cell types and subcellular compartments. PMID:27831495

Multi-scale continuum modeling of biological processes: from molecular electro-diffusion to sub-cellular signaling transduction

NASA Astrophysics Data System (ADS)

Cheng, Y.; Kekenes-Huskey, P.; Hake, J. E.; Holst, M. J.; McCammon, J. A.; Michailova, A. P.

2012-01-01

This paper presents a brief review of multi-scale modeling at the molecular to cellular scale, with new results for heart muscle cells. A finite element-based simulation package (SMOL) was used to investigate the signaling transduction at molecular and sub-cellular scales (http://mccammon.ucsd.edu/smol/, http://FETK.org) by numerical solution of the time-dependent Smoluchowski equations and a reaction-diffusion system. At the molecular scale, SMOL has yielded experimentally validated estimates of the diffusion-limited association rates for the binding of acetylcholine to mouse acetylcholinesterase using crystallographic structural data. The predicted rate constants exhibit increasingly delayed steady-state times, with increasing ionic strength, and demonstrate the role of an enzyme's electrostatic potential in influencing ligand binding. At the sub-cellular scale, an extension of SMOL solves a nonlinear, reaction-diffusion system describing Ca2+ ligand buffering and diffusion in experimentally derived rodent ventricular myocyte geometries. Results reveal the important role of mobile and stationary Ca2+ buffers, including Ca2+ indicator dye. We found that alterations in Ca2+-binding and dissociation rates of troponin C (TnC) and total TnC concentration modulate sub-cellular Ca2+ signals. The model predicts that reduced off-rate in the whole troponin complex (TnC, TnI, TnT) versus reconstructed thin filaments (Tn, Tm, actin) alters cytosolic Ca2+ dynamics under control conditions or in disease-linked TnC mutations. The ultimate goal of these studies is to develop scalable methods and theories for the integration of molecular-scale information into simulations of cellular-scale systems.

Mitochondrial dynamics and the cell cycle

USDA-ARS?s Scientific Manuscript database

Nuclear-mitochondrial (NM) communication impacts many aspects of plant development including vigor, sterility and viability. Dynamic changes in mitochondrial number, shape, size, and cellular location takes place during the cell cycle possibly impacting the process itself and leading to distribution...

Hydrodynamic size-dependent cellular uptake of aqueous QDs probed by fluorescence correlation spectroscopy.

PubMed

Dong, Chaoqing; Irudayaraj, Joseph

2012-10-11

Aqueous quantum dots (QDs) directly synthesized with various thiol ligands have been investigated as imaging probes in living cells. However, the effect of the surface chemistry of these ligands on QDs' cellular uptakes and their intracellular fate remains poorly understood. In this work, four CdTe QDs were directly synthesized under aqueous conditions using four different thiols as stabilizers and their interactions with cells were investigated. Fluorescence correlation spectroscopy (FCS), X-ray photoelectron spectroscopy (XPS), and zeta potential measurements on QDs primarily show that the surface structure of these QDs is highly dependent on the thiol ligands used in the preparation of QDs' precursors, including its layer thicknesses, densities, and surface charges. Subsequently, FCS integrated with the maximum-entropy-method-based FCS (MEMFCS) was used to investigate the concentration distribution and dynamics of these QDs in living A-427 cells. Our findings indicate that QDs' surface characteristics affect cell membrane adsorption and subsequent internalization. More critically, we show that the cellular uptake of aqueous QDs is dependent on their hydrodynamic diameter and might have the potential to escape trapped environments to accumulate in the cytoplasm.

Reduced native state stability in crowded cellular environment due to protein-protein interactions.

PubMed

Harada, Ryuhei; Tochio, Naoya; Kigawa, Takanori; Sugita, Yuji; Feig, Michael

2013-03-06

The effect of cellular crowding environments on protein structure and stability is a key issue in molecular and cellular biology. The classical view of crowding emphasizes the volume exclusion effect that generally favors compact, native states. Here, results from molecular dynamics simulations and NMR experiments show that protein crowders may destabilize native states via protein-protein interactions. In the model system considered here, mixtures of villin head piece and protein G at high concentrations, villin structures become increasingly destabilized upon increasing crowder concentrations. The denatured states observed in the simulation involve partial unfolding as well as more subtle conformational shifts. The unfolded states remain overall compact and only partially overlap with unfolded ensembles at high temperature and in the presence of urea. NMR measurements on the same systems confirm structural changes upon crowding based on changes of chemical shifts relative to dilute conditions. An analysis of protein-protein interactions and energetic aspects suggests the importance of enthalpic and solvation contributions to the crowding free energies that challenge an entropic-centered view of crowding effects.

Using the two-way shape memory effect of NiTi to control surface texture for cellular mechanotransduction

NASA Astrophysics Data System (ADS)

Liang, Yuan; Qin, Haifeng; Hou, Xiaoning; Doll, Gary L.; Ye, Chang; Dong, Yalin

2018-07-01

Mechanical force can crucially affect form and function of cells, and play critical roles in many diseases. While techniques to conveniently apply mechanical force to cells are limited, we fabricate a surface actuator prototype for cellular mechanotransduction by imparting severe plastic deformation into the surface of shape memory alloy (SMA). Using ultrasonic nanocrystal surface modification (UNSM), a deformation-based surface engineering technique with high controllability, micro surface patterns can be generated on the surface of SMA so that the micro-size cell can conform to the pattern; meanwhile, phase transformation can be induced in the subsurface by severe plastic deformation. By controlling plastic deformation and phase transformation, it is possible to establish a quantitative relation between deformation and temperature. When cells are cultured on the UNSM-treated surface, such surface can dynamically deform in response to external temperature change, and therefore apply controllable mechanical force to cells. Through this study, we demonstrate a novel way to fabricate a low-cost surface actuator that has the potential to be used for high-throughput cellular mechanotransduction.

Genetically Encoded Catalytic Hairpin Assembly for Sensitive RNA Imaging in Live Cells.

PubMed

Mudiyanselage, Aruni P K K Karunanayake; Yu, Qikun; Leon-Duque, Mark A; Zhao, Bin; Wu, Rigumula; You, Mingxu

2018-06-26

DNA and RNA nanotechnology has been used for the development of dynamic molecular devices. In particular, programmable enzyme-free nucleic acid circuits, such as catalytic hairpin assembly, have been demonstrated as useful tools for bioanalysis and to scale up system complexity to an extent beyond current cellular genetic circuits. However, the intracellular functions of most synthetic nucleic acid circuits have been hindered by challenges in the biological delivery and degradation. On the other hand, genetically encoded and transcribed RNA circuits emerge as alternative powerful tools for long-term embedded cellular analysis and regulation. Herein, we reported a genetically encoded RNA-based catalytic hairpin assembly circuit for sensitive RNA imaging inside living cells. The split version of Broccoli, a fluorogenic RNA aptamer, was used as the reporter. One target RNA can catalytically trigger the fluorescence from tens-to-hundreds of Broccoli. As a result, target RNAs can be sensitively detected. We have further engineered our circuit to allow easy programming to image various target RNA sequences. This design principle opens the arena for developing a large variety of genetically encoded RNA circuits for cellular applications.

Cell mechanics in biomedical cavitation

PubMed Central

Wang, Qianxi; Manmi, Kawa; Liu, Kuo-Kang

2015-01-01

Studies on the deformation behaviours of cellular entities, such as coated microbubbles and liposomes subject to a cavitation flow, become increasingly important for the advancement of ultrasonic imaging and drug delivery. Numerical simulations for bubble dynamics of ultrasound contrast agents based on the boundary integral method are presented in this work. The effects of the encapsulating shell are estimated by adapting Hoff's model used for thin-shell contrast agents. The viscosity effects are estimated by including the normal viscous stress in the boundary condition. In parallel, mechanical models of cell membranes and liposomes as well as state-of-the-art techniques for quantitative measurement of viscoelasticity for a single cell or coated microbubbles are reviewed. The future developments regarding modelling and measurement of the material properties of the cellular entities for cutting-edge biomedical applications are also discussed. PMID:26442142

Probing eukaryotic cell mechanics via mesoscopic simulations

PubMed Central

Shang, Menglin; Lim, Chwee Teck

2017-01-01

Cell mechanics has proven to be important in many biological processes. Although there is a number of experimental techniques which allow us to study mechanical properties of cell, there is still a lack of understanding of the role each sub-cellular component plays during cell deformations. We present a new mesoscopic particle-based eukaryotic cell model which explicitly describes cell membrane, nucleus and cytoskeleton. We employ Dissipative Particle Dynamics (DPD) method that provides us with the unified framework for modeling of a cell and its interactions in the flow. Data from micropipette aspiration experiments were used to define model parameters. The model was validated using data from microfluidic experiments. The validated model was then applied to study the impact of the sub-cellular components on the cell viscoelastic response in micropipette aspiration and microfluidic experiments. PMID:28922399

A study of the propagation, dynamics, and extinguishment of cellular flames using microgravity techniques

NASA Technical Reports Server (NTRS)

Ronney, Paul D.

1989-01-01

The characteristics of premixed gas flames in mixtures with low Lewis numbers, free of natural convection effects, were investigated and found to be dominated by diffusive-thermal instabilities. For sufficiently reactive mixtures, cellular structures resulting from these instabilities were observed and found to spawn new cells in regular patterns. For less reactive mixtures, cells formed shortly after ignition but did not spawn new cells; instead these cells evolved into a flame structure composed of stationary, apparently stable spherical flamelets. As a result of these phenomena, well-defined flammability limits were not observed. The experimental results are found to be in qualitative agreement with a simple analytical model based on the interaction of heat release due to chemical reaction, differential diffusion of thermal energy and mass, flame front curvature, and heat losses due to gas radiation.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes. Sensitivity study of the model indicated that southern and south-west part of the city have shown improvement and small patches of growth are also observed in the north western part of the city.The study highlights the growing importance of socio economic factors and geo-computational modeling approach on changing LULC of newly growing cities of modern India.

Actin cable dynamics and Rho/Rock orchestrate a polarized cytoskeletal architecture in the early steps of assembling a stratified epithelium.

PubMed

Vaezi, Alec; Bauer, Christoph; Vasioukhin, Valeri; Fuchs, Elaine

2002-09-01

To enable stratification and barrier function, the epidermis must permit self-renewal while maintaining adhesive connections. By generating K14-GFP-actin mice to monitor actin dynamics in cultured primary keratinocytes, we uncovered a role for the actin cytoskeleton in establishing cellular organization. During epidermal sheet formation, a polarized network of nascent intercellular junctions and radial actin cables assemble in the apical plane of the monolayer. These actin fibers anchor to a central actin-myosin network, creating a tension-based plane of cytoskeleton across the apical surface of the sheet. Movement of the sheet surface relative to its base expands the zone of intercellular overlap, catalyzing new sites for nascent intercellular junctions. This polarized cytoskeleton is dependent upon alpha-catenin, Rho, and Rock, and its regulation may be important for wound healing and/or stratification, where coordinated tissue movements are involved.

The Cytoskeleton-Autophagy Connection

PubMed Central

Kast, David J.; Dominguez, Roberto

2017-01-01

Summary Actin cytoskeleton dynamics plays vital roles in most forms of intracellular trafficking by promoting the biogenesis and transport of vesicular cargoes. Mounting evidence indicates that actin dynamics and membrane-cytoskeleton scaffolds also play essential roles in macroautophagy, the process by which cellular waste is isolated inside specialized vesicles called autophagosomes for recycling and degradation. Thus, branched-actin polymerization is necessary for the biogenesis of autophagosomes from the endoplasmic reticulum (ER) membrane. Actomyosin-based transport is then used to feed the growing phagophore with pre-selected cargoes and debris derived from different membranous organelles inside the cell. Mature autophagosomes then detach from the ER membrane by an unknown mechanism, and are transported and fused with lysosomes, endosomes and multi-vesicular bodies through mechanisms that involve actin- and microtubule-based motility, cytoskeleton-membrane scaffolds and signaling proteins. In this minireview, we highlight the considerable progress made recently towards understanding the diverse roles of the cytoskeleton in autophagy. PMID:28441569

[Regulation of cortical cytoskeleton dynamics during migration of free-living amoebae].

PubMed

Kłopocka, Wanda; Redowicz, Maria Jolanta; Wasik, Anna

2009-01-01

Amoeba proteus and smaller by an order of magnitude (and evolutionary younger) Acanthamoeba castellanii have been for many years model cells for studies of amoeboidal (crawling) type of movement, characteristic also for some of metazoan cells such as fibroblasts, granulocytes and macrophages. Amoeboidal migration is indispensable of organization and dynamics of actin-based cytoskeleton. While there is a number of data on molecular mechanisms of motility of A. castellanii, there is very little known about bases of migration of A. proteus. Noteworthy, a large A. proteus (length approximately 600 microm) have been from over a century an object for studies on biology and physiology of cellular migration. This review describes the current knowledge on molecular aspects of force generation required for migration of these two amoebae and attempts to compare the functioning and regulation of actin cytoskeleton in these free-living unicellular species.

DNA-controlled dynamic colloidal nanoparticle systems for mediating cellular interaction

NASA Astrophysics Data System (ADS)

Ohta, Seiichi; Glancy, Dylan; Chan, Warren C. W.

2016-02-01

Precise control of biosystems requires development of materials that can dynamically change physicochemical properties. Inspired by the ability of proteins to alter their conformation to mediate function, we explored the use of DNA as molecular keys to assemble and transform colloidal nanoparticle systems. The systems consist of a core nanoparticle surrounded by small satellites, the conformation of which can be transformed in response to DNA via a toe-hold displacement mechanism. The conformational changes can alter the optical properties and biological interactions of the assembled nanosystem. Photoluminescent signal is altered by changes in fluorophore-modified particle distance, whereas cellular targeting efficiency is increased 2.5 times by changing the surface display of targeting ligands. These concepts provide strategies for engineering dynamic nanotechnology systems for navigating complex biological environments.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Quantitative phase-contrast digital holographic microscopy for cell dynamic evaluation

NASA Astrophysics Data System (ADS)

Yu, Lingfeng; Mohanty, Samarendra; Berns, Michael W.; Chen, Zhongping

2009-02-01

The laser microbeam uses lasers to alter and/or to ablate intracellular organelles and cellular and tissue samples, and, today, has become an important tool for cell biologists to study the molecular mechanism of complex biological systems by removing individual cells or sub-cellular organelles. However, absolute quantitation of the localized alteration/damage to transparent phase objects, such as the cell membrane or chromosomes, was not possible using conventional phase-contrast or differential interference contrast microscopy. We report the development of phase-contrast digital holographic microscopy for quantitative evaluation of cell dynamic changes in real time during laser microsurgery. Quantitative phase images are recorded during the process of laser microsurgery and thus, the dynamic change in phase can be continuously evaluated. Out-of-focus organelles are re-focused by numerical reconstruction algorithms.

Structured crowding and its effects on enzyme catalysis.

PubMed

Ma, Buyong; Nussinov, Ruth

2013-01-01

Macromolecular crowding decreases the diffusion rate, shifts the equilibrium of protein-protein and protein-substrate interactions, and changes protein conformational dynamics. Collectively, these effects contribute to enzyme catalysis. Here we describe how crowding may bias the conformational change and dynamics of enzyme populations and in this way affect catalysis. Crowding effects have been studied using artificial crowding agents and in vivo-like environments. These studies revealed a correlation between protein dynamics and function in the crowded environment. We suggest that crowded environments be classified into uniform crowding and structured crowding. Uniform crowding represents random crowding conditions created by synthetic particles with a narrow size distribution. Structured crowding refers to the highly coordinated cellular environment, where proteins and other macromolecules are clustered and organized. In structured crowded environments the perturbation of protein thermal stability may be lower; however, it may still be able to modulate functions effectively and dynamically. Dynamic, allosteric enzymes could be more sensitive to cellular perturbations if their free energy landscape is flatter around the native state; on the other hand, if their free energy landscape is rougher, with high kinetic barriers separating deep minima, they could be more robust. Above all, cells are structured; and this holds both for the cytosol and for the membrane environment. The crowded environment is organized, which limits the search, and the crowders are not necessarily inert. More likely, they too transmit allosteric effects, and as such play important functional roles. Overall, structured cellular crowding may lead to higher enzyme efficiency and specificity.

The atypical Rho GTPase RhoD is a regulator of actin cytoskeleton dynamics and directed cell migration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blom, Magdalena; Reis, Katarina; Heldin, Johan

RhoD belongs to the Rho GTPases, a protein family responsible for the regulation and organization of the actin cytoskeleton, and, consequently, many cellular processes like cell migration, cell division and vesicle trafficking. Here, we demonstrate that the actin cytoskeleton is dynamically regulated by increased or decreased protein levels of RhoD. Ectopic expression of RhoD has previously been shown to give an intertwined weave of actin filaments. We show that this RhoD-dependent effect is detected in several cell types and results in a less dynamic actin filament system. In contrast, RhoD depletion leads to increased actin filament-containing structures, such as corticalmore » actin, stress fibers and edge ruffles. Moreover, vital cellular functions such as cell migration and proliferation are defective when RhoD is silenced. Taken together, we present data suggesting that RhoD is an important component in the control of actin dynamics and directed cell migration. - Highlights: • Increased RhoD expression leads to loss of actin structures, e.g. stress fibers and gives rise to decreased actin dynamics. • RhoD knockdown induces various actin-containing structures such as edge ruffles, stress fibers and cortical actin, in a cell-type specific manner. • RhoD induces specific actin rearrangements depending on its subcellular localization. • RhoD knockdown has effects on cellular processes, such as directed cell migration and proliferation.« less

Activity-based Calculation Models for the Brazilian Air Force Cellular Unit of Intendancy

DTIC Science & Technology

2013-03-01

Braz (2004), the current battlefield is fluid and dynamic. The concentration of trained personnel and suitable material in the right place at the right...Identification of budget gaps; f) Elimination of superfluous activities; g) Selection of lower cost activities; h) Reduction of the time or the resources...x - x - 4 33% 8.4 Delivery mail - x x x x - - - x - x - 6 50% 9. Recreational facilities 9.1 Provide space and activities to entertainment x x

Opinion evolution in open community

NASA Astrophysics Data System (ADS)

Pan, Qiuhui; Qin, Yao; Xu, Yiqun; Tong, Mengfei; He, Mingfeng

We consider a dynamic group composed with a constant number of people and the people will change periodically. Every member in the community owns a value of confidence — a mechanism that measures the agent’s coherence to his or her own attitude. Based on Cellular Automata, the opinions of all agents are synchronously updated. As long as the updating frequency and updating proportion are appropriate, the open system can reach a democracy-like steady state. The majority of agents in the community will hold the same opinion.

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.

PubMed

Meadows, Adam L; Karnik, Rahi; Lam, Harry; Forestell, Sean; Snedecor, Brad

2010-03-01

We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer. (c) 2009 Elsevier Inc. All rights reserved.

Unique Cellular Organization in the Oldest Root Meristem.

PubMed

Hetherington, Alexander J; Dubrovsky, Joseph G; Dolan, Liam

2016-06-20

Roots and shoots of plant bodies develop from meristems-cell populations that self-renew and produce cells that undergo differentiation-located at the apices of axes [1].The oldest preserved root apices in which cellular anatomy can be imaged are found in nodules of permineralized fossil soils called coal balls [2], which formed in the Carboniferous coal swamp forests over 300 million years ago [3-9]. However, no fossil root apices described to date were actively growing at the time of preservation [3-10]. Because the cellular organization of meristems changes when root growth stops, it has been impossible to compare cellular dynamics as stem cells transition to differentiated cells in extinct and extant taxa [11]. We predicted that meristems of actively growing roots would be preserved in coal balls. Here we report the discovery of the first fossilized remains of an actively growing root meristem from permineralized Carboniferous soil with detail of the stem cells and differentiating cells preserved. The cellular organization of the meristem is unique. The position of the Körper-Kappe boundary, discrete root cap, and presence of many anticlinal cell divisions within a broad promeristem distinguish it from all other known root meristems. This discovery is important because it demonstrates that the same general cellular dynamics are conserved between the oldest extinct and extant root meristems. However, its unique cellular organization demonstrates that extant root meristem organization and development represents only a subset of the diversity that has existed since roots first evolved. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Z-cad dual fluorescent sensor detects dynamic changes between the epithelial and mesenchymal cellular states.

PubMed

Toneff, M J; Sreekumar, A; Tinnirello, A; Hollander, P Den; Habib, S; Li, S; Ellis, M J; Xin, L; Mani, S A; Rosen, J M

2016-06-17

The epithelial to mesenchymal transition (EMT) has been implicated in metastasis and therapy resistance of carcinomas and can endow cancer cells with cancer stem cell (CSC) properties. The ability to detect cancer cells that are undergoing or have completed EMT has typically relied on the expression of cell surface antigens that correlate with an EMT/CSC phenotype. Alternatively these cells may be permanently marked through Cre-mediated recombination or through immunostaining of fixed cells. The EMT process is dynamic, and these existing methods cannot reveal such changes within live cells. The development of fluorescent sensors that mirror the dynamic EMT state by following the expression of bona fide EMT regulators in live cells would provide a valuable new tool for characterizing EMT. In addition, these sensors will allow direct observation of cellular plasticity with respect to the epithelial/mesenchymal state to enable more effective studies of EMT in cancer and development. We generated a lentiviral-based, dual fluorescent reporter system, designated as the Z-cad dual sensor, comprising destabilized green fluorescent protein containing the ZEB1 3' UTR and red fluorescent protein driven by the E-cadherin (CDH1) promoter. Using this sensor, we robustly detected EMT and mesenchymal to epithelial transition (MET) in breast cancer cells by flow cytometry and fluorescence microscopy. Importantly, we observed dynamic changes in cellular populations undergoing MET. Additionally, we used the Z-cad sensor to identify and isolate minor subpopulations of cells displaying mesenchymal properties within a population comprising predominately epithelial-like cells. The Z-cad dual sensor identified cells with CSC-like properties more effectively than either the ZEB1 3' UTR or E-cadherin sensor alone. The Z-cad dual sensor effectively reports the activities of two factors critical in determining the epithelial/mesenchymal state of carcinoma cells. The ability of this stably integrating dual sensor system to detect dynamic fluctuations between these two states through live cell imaging offers a significant improvement over existing methods and helps facilitate the study of EMT/MET plasticity in response to different stimuli and in cancer pathogenesis. Finally, the versatile Z-cad sensor can be adapted to a variety of in vitro or in vivo systems to elucidate whether EMT/MET contributes to normal and disease phenotypes.

The integrin alphav beta3 increases cellular stiffness and cytoskeletal remodeling dynamics to facilitate cancer cell invasion

NASA Astrophysics Data System (ADS)

Mierke, Claudia Tanja

2013-01-01

The process of cancer cell invasion through the extracellular matrix (ECM) of connective tissue plays a prominent role in tumor progression and is based fundamentally on biomechanics. Cancer cell invasion usually requires cell adhesion to the ECM through the cell-matrix adhesion receptors integrins. The expression of the αvβ3 integrin is increased in several tumor types and is consistently associated with increased metastasis formation in patients. The hypothesis was that the αvβ3 integrin expression increases the invasiveness of cancer cells through increased cellular stiffness, and increased cytoskeletal remodeling dynamics. Here, the invasion of cancer cells with different αvβ3 integrin expression levels into dense three-dimensional (3D) ECMs has been studied. Using a cell sorter, two subcell lines expressing either high or low amounts of αvβ3 integrins (αvβ3high or αvβ3low cells, respectively) have been isolated from parental MDA-MB-231 breast cancer cells. αvβ3high cells showed a threefold increased cell invasion compared to αvβ3low cells. Similar results were obtained for A375 melanoma, 786-O kidney and T24 bladder carcinoma cells, and cells in which the β3 integrin subunit was knocked down using specific siRNA. To investigate whether contractile forces are essential for αvβ3 integrin-mediated increased cellular stiffness and subsequently enhanced cancer cell invasion, invasion assays were performed in the presence of myosin light chain kinase inhibitor ML-7 and Rho kinase inhibitor Y27632. Indeed, cancer cell invasiveness was reduced after addition of ML-7 and Y27632 in αvβ3high cells but not in αvβ3low cells. Moreover, after addition of the contractility enhancer calyculin A, an increase in pre-stress in αvβ3low cells was observed, which enhanced cellular invasiveness. In addition, inhibition of the Src kinase, STAT3 or Rac1 strongly reduced the invasiveness of αvβ3high cells, whereas the invasiveness of β3 specific knock-down cells and αvβ3low cells was not altered. In summary, these results suggest that the αvβ3 integrin enhances cancer cell invasion through increased cellular stiffness and enhanced cytoskeletal remodeling dynamics, which enables the cells to generate and transmit contractile forces to overcome the steric hindrance of 3D ECMs.

Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel Adrian; Oprisan, Ana

2005-03-01

Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Confocal reflectance quantitative phase microscope system for cellular membranes dynamics study (Conference Presentation)

NASA Astrophysics Data System (ADS)

Singh, Vijay Raj; Yaqoob, Zahid; So, Peter T. C.

2017-02-01

Quantitative phase microscopy (QPM) techniques developed so far primarily belongs to high speed transmitted light based systems that has enough sensitivity to resolve membrane fluctuations and dynamics, but has no depth resolution. Therefore, most biomechanics studies using QPM today is confined to simple cells, such as RBCs, without internal organelles. An important instrument that will greatly extend the biomedical applications of QPM is to develop next generation microscope with 3D capability and sufficient temporal resolution to study biomechanics of complex eukaryotic cells including the mechanics of their internal compartments. For eukaryotic cells, the depth sectioning capability is critical and should be sufficient to distinguish nucleic membrane fluctuations from plasma membrane fluctuations. Further, this microscope must provide high temporal resolution since typical eukaryotes membranes are substantially stiffer than RBCs. A confocal reflectance quantitative phase microscope is presented based on multi-pinhole scanning, with the capabilities of higher temporal resolution and sensitivity for nucleic and plasma membranes of eukaryotic cells. System hardware is developed based on an array of confocal pinhole generated by using the `ON' state of subset of micro-mirrors of digital micro-mirror device (DMD, from Texas Instruments) and high-speed raster scanning provides 14ms imaging speed in wide-field mode. A common path interferometer is integrated at the imaging arm for detection of specimens' quantitative phase information. Theoretical investigation of quantitative phase reconstructed from system is investigated and application of system is presented for dimensional fluctuations measurements of both cellular plasma and nucleic membranes of embryonic stem cells.

Dynamism & Detail

ERIC Educational Resources Information Center

Flannery, Maura C.

2004-01-01

New material discovered in the study of cell research is presented for the benefit of biology teachers. Huge amounts of data are being generated in fields like cellular dynamics, and it is felt that people's understanding of the cell is becoming much more complex and detailed.

CAM: A high-performance cellular-automaton machine

NASA Astrophysics Data System (ADS)

Toffoli, Tommaso

1984-01-01

CAM is a high-performance machine dedicated to the simulation of cellular automata and other distributed dynamical systems. Its speed is about one-thousand times greater than that of a general-purpose computer programmed to do the same task; in practical terms, this means that CAM can show the evolution of cellular automata on a color monitor with an update rate, dynamic range, and spatial resolution comparable to those of a Super-8 movie, thus permitting intensive interactive experimentation. Machines of this kind can open up novel fields of research, and in this context it is important that results be easy to obtain, reproduce, and transmit. For these reasons, in designing CAM it was important to achieve functional simplicity, high flexibility, and moderate production cost. We expect that many research groups will be able to own their own copy of the machine to do research with.

A dynamically reconfigurable logic cell: from artificial neural networks to quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Naqvi, Syed Rameez; Akram, Tallha; Iqbal, Saba; Haider, Sajjad Ali; Kamran, Muhammad; Muhammad, Nazeer

2018-02-01

Considering the lack of optimization support for Quantum-dot Cellular Automata, we propose a dynamically reconfigurable logic cell capable of implementing various logic operations by means of artificial neural networks. The cell can be reconfigured to any 2-input combinational logic gate by altering the strength of connections, called weights and biases. We demonstrate how these cells may appositely be organized to perform multi-bit arithmetic and logic operations. The proposed work is important in that it gives a standard implementation of an 8-bit arithmetic and logic unit for quantum-dot cellular automata with minimal area and latency overhead. We also compare the proposed design with a few existing arithmetic and logic units, and show that it is more area efficient than any equivalent available in literature. Furthermore, the design is adaptable to 16, 32, and 64 bit architectures.

A comprehensive model of the spatio-temporal stem cell and tissue organisation in the intestinal crypt.

PubMed

Buske, Peter; Galle, Jörg; Barker, Nick; Aust, Gabriela; Clevers, Hans; Loeffler, Markus

2011-01-06

We introduce a novel dynamic model of stem cell and tissue organisation in murine intestinal crypts. Integrating the molecular, cellular and tissue level of description, this model links a broad spectrum of experimental observations encompassing spatially confined cell proliferation, directed cell migration, multiple cell lineage decisions and clonal competition.Using computational simulations we demonstrate that the model is capable of quantitatively describing and predicting the dynamic behaviour of the intestinal tissue during steady state as well as after cell damage and following selective gain or loss of gene function manipulations affecting Wnt- and Notch-signalling. Our simulation results suggest that reversibility and flexibility of cellular decisions are key elements of robust tissue organisation of the intestine. We predict that the tissue should be able to fully recover after complete elimination of cellular subpopulations including subpopulations deemed to be functional stem cells. This challenges current views of tissue stem cell organisation.

Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

NASA Astrophysics Data System (ADS)

McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

2014-03-01

Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Dynamic fragmentation of cellular, ice-templated alumina scaffolds

DOE PAGES

Tan, Yi Ming; Cervantes, Octavio; Nam, SeanWoo; ...

2016-01-08

Here, we examine the dynamic failure of ice-templated freeze-cast alumina scaffolds that are being considered as biomimetic hierarchical structures. Three porosities of alumina freeze-cast structures were fabricated, and a systematic variation in microstructural properties such as lamellar width and thickness was observed with changing porosity. Dynamic impact tests were performed in a light-gas gun to examine the failure properties of these materials under high strain-rate loading. Nearly complete delamination was observed following impact, along with characteristic cracking across the lamellar width. Average fragment size decreases with increasing porosity, and a theoretical model was developed to explain this behavior based onmore » microstructural changes. Using an energy balance between kinetic, strain, and surface energies within a single lamella, we are able to accurately predict the characteristic fragment size using only standard material properties of bulk alumina.« less

A Complex Endomembrane System in the Archaeon Ignicoccus hospitalis Tapped by Nanoarchaeum equitans

DOE PAGES

Heimerl, Thomas; Flechsler, Jennifer; Pickl, Carolin; ...

2017-06-13

Based on serial sectioning, focused ion beam scanning electron microscopy (FIB/SEM), and electron tomography, we depict in detail the highly unusual anatomy of the marine hyperthermophilic crenarchaeon, Ignicoccus hospitalis. Our data support a complex and dynamic endomembrane system consisting of cytoplasmic protrusions, and with secretory function. Moreover, we reveal that the cytoplasm of the putative archaeal ectoparasite Nanoarchaeum equitans can get in direct contact with this endomembrane system, complementing and explaining recent proteomic, transcriptomic and metabolomic data on this inter-archaeal relationship. In addition, we identified a matrix of filamentous structures and/or tethers in the voluminous inter-membrane compartment (IMC) of I.more » hospitalis, which might be responsible for membrane dynamics. Overall, this unusual cellular compartmentalization, ultrastructure and dynamics in an archaeon that belongs to the recently proposed TACK superphylum prompts speculation that the eukaryotic endomembrane system might originate from Archaea.« less

Modeling infectious disease dynamics in the complex landscape of global health

PubMed Central

Heesterbeek, Hans; Anderson, Roy; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken; Edmunds, John; Frost, Simon; Funk, Sebastian; Hollingsworth, Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James; Metcalf, Jessica; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet; Roberts, Mick; Viboud, Cecile

2015-01-01

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational and spatial scales, which even within a single pathogen often span hours to months, cellular to ecosystem levels, and local to pandemic spread. Some pathogens are directly transmitted between individuals of a single species, while others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity, and dynamic human behavior, raise prevention and control from formerly national to international issues. In the face of this complexity, mathematical models offer essential tools for synthesizing information to understand epidemiological patterns, and for developing the quantitative evidence base for decision-making in global health. PMID:25766240

Dynamics of beta-amyloid peptide in cholesterol superlattice domain

NASA Astrophysics Data System (ADS)

Smirnov, Anton; Zhu, Qing; Vaughn, Mark; Khare, Rajesh; Cheng, K.

2006-10-01

Presence of beta-amyloid peptide (beta-A) plagues in membranes of neuron cells is a clinical signature of Alzheimer disease. The onset of beta-A peptide aggregation occurs via a conformational transition from an alpha-helix state to a beta-sheet state. A gradual build-up of beta-A content in the neuronal extracellular space is another characteristic of the beta-A plague formation. Hypothetically, both the pathological conformation and the predominant localization of the beta-A can be a result of specific dynamic characteristics of the interphase between cellular membrane and extracellular milieu. In this study, the beta-A interphase problem has been investigated using a virtual membrane model implemented on the base of GROMACS molecular dynamics simulation package. The detailed folding pattern of beta-A has been examined using a novice interphase model comprised of a cholesterol supperlattice membrane and two water layers.

Cellular Tug-of-War: Forces at Work and DNA Stretching in Mitosis

NASA Astrophysics Data System (ADS)

Griffin, Brian; Kilfoil, Maria L.

2013-03-01

In the microscopic world of the cell dominated by thermal noise, a cell must be able to successfully segregate its DNA with high fidelity in order to pass its genetic information on to its progeny. In this process of mitosis in eukaryotes, driving forces act on the cytoskeleton-based architecture called the mitotic spindle to promote this division. Our preliminary data demonstrates that the dynamics of this process in yeast cells is universal. Moreover, the dynamics suggest an increasing load as the chromosomes are pulled apart. To investigate this, we use three-dimensional imaging to track the dynamics of the poles of this architecture and the points of attachment to chromosomes simultaneously and with high spatial resolution. We analyze the relative motions of chromosomes as they are organized before segregation and as they are pulled apart, using this data to investigate the force-response behavior of this cytoskeleton-chromosome polymer system.

Generalized Synchronization in AN Array of Nonlinear Dynamic Systems with Applications to Chaotic Cnn

NASA Astrophysics Data System (ADS)

Min, Lequan; Chen, Guanrong

This paper establishes some generalized synchronization (GS) theorems for a coupled discrete array of difference systems (CDADS) and a coupled continuous array of differential systems (CCADS). These constructive theorems provide general representations of GS in CDADS and CCADS. Based on these theorems, one can design GS-driven CDADS and CCADS via appropriate (invertible) transformations. As applications, the results are applied to autonomous and nonautonomous coupled Chen cellular neural network (CNN) CDADS and CCADS, discrete bidirectional Lorenz CNN CDADS, nonautonomous bidirectional Chua CNN CCADS, and nonautonomously bidirectional Chen CNN CDADS and CCADS, respectively. Extensive numerical simulations show their complex dynamic behaviors. These theorems provide new means for understanding the GS phenomena of complex discrete and continuously differentiable networks.

Dynamic Analysis of the Melanoma Model: From Cancer Persistence to Its Eradication

NASA Astrophysics Data System (ADS)

Starkov, Konstantin E.; Jimenez Beristain, Laura

In this paper, we study the global dynamics of the five-dimensional melanoma model developed by Kronik et al. This model describes interactions of tumor cells with cytotoxic T cells and respective cytokines under cellular immunotherapy. We get the ultimate upper and lower bounds for variables of this model, provide formulas for equilibrium points and present local asymptotic stability/hyperbolic instability conditions. Next, we prove the existence of the attracting set. Based on these results we come to global asymptotic melanoma eradication conditions via global stability analysis. Finally, we provide bounds for a locus of the melanoma persistence equilibrium point, study the case of melanoma persistence and describe conditions under which we observe global attractivity to the unique melanoma persistence equilibrium point.

Reversible Nuclear-Lipid-Droplet Morphology Induced by Oleic Acid: A Link to Cellular-Lipid Metabolism

PubMed Central

Lagrutta, Lucía C.; Montero-Villegas, Sandra; Layerenza, Juan P.; Sisti, Martín S.; García de Bravo, Margarita M.

2017-01-01

Neutral lipids—involved in many cellular processes—are stored as lipid droplets (LD), those mainly cytosolic (cLD) along with a small nuclear population (nLD). nLD could be involved in nuclear-lipid homeostasis serving as an endonuclear buffering system that would provide or incorporate lipids and proteins involved in signalling pathways as transcription factors and as enzymes of lipid metabolism and nuclear processes. Our aim was to determine if nLD constituted a dynamic domain. Oleic-acid (OA) added to rat hepatocytes or HepG2 cells in culture produced cellular-phenotypic LD modifications: increases in TAG, CE, C, and PL content and in cLD and nLD numbers and sizes. LD increments were reversed on exclusion of OA and were prevented by inhibition of acyl-CoA synthetase (with Triacsin C) and thus lipid biosynthesis. Under all conditions, nLD corresponded to a small population (2–10%) of total cellular LD. The anabolism triggered by OA, involving morphologic and size changes within the cLD and nLD populations, was reversed by a net balance of catabolism, upon eliminating OA. These catabolic processes included lipolysis and the mobilization of hydrolyzed FA from the LD to cytosolic-oxidation sites. These results would imply that nLD are actively involved in nuclear processes that include lipids. In conclusion, nLD are a dynamic nuclear domain since they are modified by OA through a reversible mechanism in combination with cLD; this process involves acyl-CoA-synthetase activity; ongoing TAG, CE, and PL biosynthesis. Thus, liver nLD and cLD are both dynamic cellular organelles. PMID:28125673

Towards a perceptive understanding of size in cellular biology.

PubMed

Zoppè, Monica

2017-06-29

Cells are minute-typically too small to be seen by the human eye. Even so, the cellular world encompasses a range of scales, from roughly a tenth of a nanometer (10 -10 m) to a millimeter (10 -3 m) or larger, spanning seven orders of magnitude or more. Because they are so far from our experience, it is difficult for us to envision such scales. To help our imagination grasp such dimensions, I propose the adoption of a 'perceptive scale' that can facilitate a more direct experience of cellular sizes. From this, as I argue below, will stem a new perception also of biological shape, cellular space and dynamic processes.

Cellular Precipitates Of Iron Oxide in Olivine in a Stratospheric Interplanetary Dust Particle

NASA Technical Reports Server (NTRS)

Rietmeijer, Frans J. M.

1996-01-01

The petrology of a massive olivine-sulphide interplanetary dust particle shows melting of Fe,Ni-sulphide plus complete loss of sulphur and subsequent quenching to a mixture of iron-oxides and Fe,Ni-metal. Oxidation of the fayalite component in olivine produced maghemite discs and cellular intergrowths with olivine and rare andradite-rich garnet. Cellular reactions require no long-range solid-state diffusion and are kinetically favourable during pyrometamorphic oxidation. Local melting of the cellular intergrowths resulted in three dimensional symplectic textures. Dynamic pyrometamorphism of this asteroidal particle occurred at approx. 1100 C during atmospheric entry flash (5-15 s) heating.

Soliton cellular automaton associated with Dn(1)-crystal B2,s

NASA Astrophysics Data System (ADS)

Misra, Kailash C.; Wilson, Evan A.

2013-04-01

A solvable vertex model in ferromagnetic regime gives rise to a soliton cellular automaton which is a discrete dynamical system in which site variables take on values in a finite set. We study the scattering of a class of soliton cellular automata associated with the U_q(D_n^{(1)})-perfect crystal B2, s. We calculate the combinatorial R matrix for all elements of B2, s ⊗ B2, 1. In particular, we show that the scattering rule for our soliton cellular automaton can be identified with the combinatorial R matrix for U_q(A_1^{(1)}) oplus U_q(D_{n-2}^{(1)})-crystals.

Analysis of soybean tissue culture protein dynamics using difference gel electrophoresis.

PubMed

Miernyk, Ján A; Jett, Alissa A; Johnston, Mark L

2016-01-01

Excised hypocotyls from developing soybean (Glycine max (L.) merr. cv. Jack) were cultivated on agar-solidified medium until callus formed. The calli were then propagated in liquid medium until stable, relatively uniform, finely-divided suspension cultures were obtained. Cells were typically transferred to fresh medium at 7-day intervals. Cultures were harvested by filtration five days (early log phase) or eight days (late log phase) after transfer. In order to evaluate dynamic changes, both intracellular and extracellular proteins were analyzed by 2-dimensional difference gel electrophoresis. Selected spots were subjected to in-gel tryptic-digestion and the resultant peptides were analyzed by nLC-MS/MS. In follow-up studies gel-free shot-gun analyses led to identification of 367 intracellular proteins and 188 extracellular proteins. The significance of the described research is two-fold. First a gel-based proteomics method was applied to the study of the dynamics of the secretome (extracellular proteins). Second, results of a shot-gun non-gel based proteomic survey of both cellular and extracellular proteins are presented. Published by Elsevier B.V.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Na; Zhang, Peng; Kang, Wei

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics.

PubMed

Scifo, Enzo; Calza, Giulio; Fuhrmann, Martin; Soliymani, Rabah; Baumann, Marc; Lalowski, Maciej

2017-06-01

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Magnetic resonance imaging findings of cellular angiofibroma of the tunica vaginalis of the testis: a case report.

PubMed

Ntorkou, Alexandra A; Tsili, Athina C; Giannakis, Dimitrios; Batistatou, Anna; Stavrou, Sotirios; Sofikitis, Nikolaos; Argyropoulou, Maria I

2016-03-31

Cellular angiofibroma represents a rare mesenchymal tumor typically involving the inguinoscrotal area in middle-aged men. Although the origin of this benign tumor is unknown, it is histologically classified as an angiomyxoid tumor. Cellular angiofibroma is characterized by a diversity of pathological and imaging features. An accurate preoperative diagnosis is challenging. Magnetic resonance imaging examination of the scrotum has been reported as a valuable adjunct modality in the investigation of scrotal pathology. The technique by providing both structural and functional information is useful in the differentiation between extratesticular and intratesticular diseases and in the preoperative characterization of the histologic nature of various scrotal lesions. There are few reports in the English literature addressing the magnetic resonance imaging findings of cellular angiofibroma of the scrotum and no reports on functional magnetic resonance imaging data. Here we present the first case of a cellular angiofibroma arising from the tunica vaginalis of the testis and we discuss the value of a multiparametric magnetic resonance protocol, including diffusion-weighted imaging, magnetization transfer imaging and dynamic contrast-enhanced magnetic resonance imaging in the preoperative diagnosis of this rare neoplasm. A 47-year Greek man presented with a painless left scrotal swelling, which had gradually enlarged during the last 6 months. Magnetic resonance imaging of his scrotum displayed a left paratesticular mass, in close proximity to the tunica vaginalis, with heterogeneous high signal intensity on T2-weighted images and no areas of restricted diffusion. The tumor was hypointense on magnetization transfer images, suggestive for the presence of macromolecules. On dynamic contrast-enhanced magnetic resonance imaging the mass showed intense heterogeneous enhancement with a type II curve. Magnetic resonance imaging findings were strongly suggestive of a benign paratesticular tumor, which was confirmed on pathology following lesion excision. Magnetic resonance imaging of the scrotum by combining conventional and functional magnetic resonance data provides useful diagnostic information in the preoperative characterization of scrotal masses. A possible diagnosis of a benign paratesticular tumor based on magnetic resonance imaging features may improve patient care and decrease the number of unnecessary radical surgical explorations.

Challenges in structural approaches to cell modeling

PubMed Central

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A.

2016-01-01

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. PMID:27255863

Physical biology of human brain development.

PubMed

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2015-01-01

Neurodevelopment is a complex, dynamic process that involves a precisely orchestrated sequence of genetic, environmental, biochemical, and physical events. Developmental biology and genetics have shaped our understanding of the molecular and cellular mechanisms during neurodevelopment. Recent studies suggest that physical forces play a central role in translating these cellular mechanisms into the complex surface morphology of the human brain. However, the precise impact of neuronal differentiation, migration, and connection on the physical forces during cortical folding remains unknown. Here we review the cellular mechanisms of neurodevelopment with a view toward surface morphogenesis, pattern selection, and evolution of shape. We revisit cortical folding as the instability problem of constrained differential growth in a multi-layered system. To identify the contributing factors of differential growth, we map out the timeline of neurodevelopment in humans and highlight the cellular events associated with extreme radial and tangential expansion. We demonstrate how computational modeling of differential growth can bridge the scales-from phenomena on the cellular level toward form and function on the organ level-to make quantitative, personalized predictions. Physics-based models can quantify cortical stresses, identify critical folding conditions, rationalize pattern selection, and predict gyral wavelengths and gyrification indices. We illustrate that physical forces can explain cortical malformations as emergent properties of developmental disorders. Combining biology and physics holds promise to advance our understanding of human brain development and enable early diagnostics of cortical malformations with the ultimate goal to improve treatment of neurodevelopmental disorders including epilepsy, autism spectrum disorders, and schizophrenia.

A network approach to the geometric structure of shallow cloud fields

NASA Astrophysics Data System (ADS)

Glassmeier, F.; Feingold, G.

2017-12-01

The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations. As an outlook, we discuss how a similar network approach can be applied to describe and quantify the geometric structure of shallow cumulus cloud fields.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Country-wide rainfall maps from cellular communication networks

PubMed Central

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

2013-01-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

Free-Energy-Based Protein Design: Re-Engineering Cellular Retinoic Acid Binding Protein II Assisted by the Moveable-Type Approach.

PubMed

Zhong, Haizhen A; Santos, Elizabeth M; Vasileiou, Chrysoula; Zheng, Zheng; Geiger, James H; Borhan, Babak; Merz, Kenneth M

2018-03-14

How to fine-tune the binding free energy of a small-molecule to a receptor site by altering the amino acid residue composition is a key question in protein engineering. Indeed, the ultimate solution to this problem, to chemical accuracy (±1 kcal/mol), will result in profound and wide-ranging applications in protein design. Numerous tools have been developed to address this question using knowledge-based models to more computationally intensive molecular dynamics simulations-based free energy calculations, but while some success has been achieved there remains room for improvement in terms of overall accuracy and in the speed of the methodology. Here we report a fast, knowledge-based movable-type (MT)-based approach to estimate the absolute and relative free energy of binding as influenced by mutations in a small-molecule binding site in a protein. We retrospectively validate our approach using mutagenesis data for retinoic acid binding to the Cellular Retinoic Acid Binding Protein II (CRABPII) system and then make prospective predictions that are borne out experimentally. The overall performance of our approach is supported by its success in identifying mutants that show high or even sub-nano-molar binding affinities of retinoic acid to the CRABPII system.

Geometric phase transition in the cellular network of the pancreatic islets may underlie the onset of type 1diabetes

NASA Astrophysics Data System (ADS)

Wang, Xujing

Living systems are characterized by complexity in structure and emergent dynamic orders. In many aspects the onset of a chronic disease resembles phase transition in a dynamic system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we investigate this idea in a real example, the insulin-producing pancreatic islet β-cells and the onset of type 1 diabetes. Within each islet, the β-cells are electrically coupled to each other, and function as a network with synchronized actions. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity, and the critical point where the islet cellular network loses site percolation, is consistent with laboratory and clinical observations of the threshold β-cell loss that causes islet functional failure. Numerical simulations confirm that the islet cellular network needs to be percolated for β-cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after disease onset and introduction of treatment, potentially explaining a long time mystery in the clinical study of type 1 diabetes: the honeymoon phenomenon. Based on these results, we hypothesized that the onset of T1D may be the result of a phase transition of the islet β-cell network. We further discuss the potential applications in identifying disease-driving factors, and the critical parameters that are predictive of disease onset.

A quantum Samaritan’s dilemma cellular automaton

PubMed Central

Situ, Haozhen

2017-01-01

The dynamics of a spatial quantum formulation of the iterated Samaritan’s dilemma game with variable entangling is studied in this work. The game is played in the cellular automata manner, i.e. with local and synchronous interaction. The game is assessed in fair and unfair contests, in noiseless scenarios and with disrupting quantum noise. PMID:28680654

Rho GTPases at the crossroad of signaling networks in mammals

PubMed Central

Wojnacki, José; Quassollo, Gonzalo; Marzolo, María-Paz; Cáceres, Alfredo

2014-01-01

Microtubule (MT) organization and dynamics downstream of external cues is crucial for maintaining cellular architecture and the generation of cell asymmetries. In interphase cells RhoA, Rac, and Cdc42, conspicuous members of the family of small Rho GTPases, have major roles in modulating MT stability, and hence polarized cell behaviors. However, MTs are not mere targets of Rho GTPases, but also serve as signaling platforms coupling MT dynamics to Rho GTPase activation in a variety of cellular conditions. In this article, we review some of the key studies describing the reciprocal relationship between small Rho-GTPases and MTs during migration and polarization. PMID:24691223

Cellular Biotechnology Operations Support System Fluid Dynamics Investigation

NASA Technical Reports Server (NTRS)

2003-01-01

Aboard the International Space Station (ISS), the Tissue Culture Medium (TCM) is the bioreactor vessel in which cell cultures are grown. With its two syringe ports, it is much like a bag used to administer intravenous fluid, except it allows gas exchange needed for life. The TCM contains cell culture medium, and when frozen cells are flown to the ISS, they are thawed and introduced to the TCM through the syringe ports. In the Cellular Biotechnology Operations Support System-Fluid Dynamics Investigation (CBOSS-FDI) experiment, several mixing procedures are being assessed to determine which method achieves the most uniform mixing of growing cells and culture medium.

Dynamic Spectrum Access for Internet of Things Service in Cognitive Radio-Enabled LPWANs

PubMed Central

Moon, Bongkyo

2017-01-01

In this paper, we focus on a dynamic spectrum access strategy for Internet of Things (IoT) applications in two types of radio systems: cellular networks and cognitive radio-enabled low power wide area networks (CR-LPWANs). The spectrum channel contention between the licensed cellular networks and the unlicensed CR-LPWANs, which work with them, only takes place within the cellular radio spectrum range. Our aim is to maximize the spectrum capacity for the unlicensed users while ensuring that it never interferes with the licensed network. Therefore, in this paper we propose a dynamic spectrum access strategy for CR-LPWANs operating in both licensed and unlicensed bands. The simulation and the numerical analysis by using a matrix geometric approach for the strategy are presented. Finally, we obtain the blocking probability of the licensed users, the mean dwell time of the unlicensed user, and the total carried traffic and combined service quality for the licensed and unlicensed users. The results show that the proposed strategy can maximize the spectrum capacity for the unlicensed users using IoT applications as well as keep the service quality of the licensed users independent of them. PMID:29206215

In vivo dynamical behavior of yeast chromatin modeled as an entangled polymer network with constraint release

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Kilfoil, Maria L.

2013-03-01

The high fidelity segregation of chromatin is the central problem in cell mitosis. The role of mechanics underlying this, however, is undetermined. Work in this area has largely focused on cytoskeletal elements of the process. Preliminary work in our lab suggests the mechanical properties of chromatin are fundamental in this process. Nevertheless, the mechanical properties of chromatin in the cellular context are not well-characterized. For better understanding of the role of mechanics in this cellular process, and of the chromatin mechanics in vivo generally, a systematic dynamical description of chromatin in vivo is required. Accordingly, we label specific sites on chromatin with fluorescent proteins of different wave lengths, enabling us to detect multiple spots separately in 3D and track their displacements in time inside living yeast cells. We analyze the pairwise cross-correlated motion between spots as a function of relative distance along the DNA contour. Comparison between the reptation model and our data serves to test our conjecture that chromatin in the cell is basically an entangled polymer network under constraints to thermal motion, and removal of constraints by non-thermal cellular processes is expected to affect its dynamic behavior.

Dynamic Spectrum Access for Internet of Things Service in Cognitive Radio-Enabled LPWANs.

PubMed

Moon, Bongkyo

2017-12-05

In this paper, we focus on a dynamic spectrum access strategy for Internet of Things (IoT) applications in two types of radio systems: cellular networks and cognitive radio-enabled low power wide area networks (CR-LPWANs). The spectrum channel contention between the licensed cellular networks and the unlicensed CR-LPWANs, which work with them, only takes place within the cellular radio spectrum range. Our aim is to maximize the spectrum capacity for the unlicensed users while ensuring that it never interferes with the licensed network. Therefore, in this paper we propose a dynamic spectrum access strategy for CR-LPWANs operating in both licensed and unlicensed bands. The simulation and the numerical analysis by using a matrix geometric approach for the strategy are presented. Finally, we obtain the blocking probability of the licensed users, the mean dwell time of the unlicensed user, and the total carried traffic and combined service quality for the licensed and unlicensed users. The results show that the proposed strategy can maximize the spectrum capacity for the unlicensed users using IoT applications as well as keep the service quality of the licensed users independent of them.

Integrated Experimental and Model-based Analysis Reveals the Spatial Aspects of EGFR Activation Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankaran, Harish; Zhang, Yi; Chrisler, William B.

2012-10-02

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerizationmore » and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks.« less

A microfabricated platform with hydrogel arrays for 3D mechanical stimulation of cells.

PubMed

Liu, Haijiao; Usprech, Jenna; Sun, Yu; Simmons, Craig A

2016-04-01

Cellular microenvironments present cells with multiple stimuli, including not only soluble biochemical and insoluble matrix cues but also mechanical factors. Biomaterial array platforms have been used to combinatorially and efficiently probe and define two-dimensional (2D) and 3D microenvironmental cues to guide cell functions for tissue engineering applications. However, there are few examples of array platforms that include dynamic mechanical forces, particularly to enable stretching of 3D cell-seeded biomaterials, which is relevant to engineering connective and cardiovascular tissues. Here we present a deformable membrane platform that enables 3D dynamic mechanical stretch of arrayed biomaterial constructs. Cell-seeded polyethylene glycol norbornene (PEG-NB) hydrogels were bound to miniaturized deformable membranes via a thiol-ene reaction with off-stoichiometry thiol-ene based polydimethylsiloxane (OSTE-PDMS) as the membrane material. Bonding to OSTE-PDMS enabled the 3D hydrogel microconstructs to be cyclically deformed and stretched by the membrane. As a first demonstration, human mesenchymal stromal cells (MSCs) embedded in PEG-NB were stretched for several days. They were found to be viable, spread in the 3D hydrogels, and exhibited a contractile myofibroblast phenotype when exposed to dynamic 3D mechanical deformation. This platform, which is readily scalable to larger arrays, enables systematic interrogation of the relationships between combinations of 3D mechanobiological cues and cellular responses, and thus has the potential to identify strategies to predictably control the construction of functional engineered tissues. Current high-throughput biomaterial screening approaches fail to consider the effects of dynamic mechanical stimulation, despite its importance in a wide variety of regenerative medicine applications. To meet this need, we developed a deformable membrane platform that enables 3D dynamic stretch of arrayed biomaterial constructs. Our approach combines microtechnologies fabricated with off-stoichiometry thiol-ene based polydimethylsiloxane membranes that can covalently bond cell-seeded polyethylene glycol norbornene 3D hydrogels, a model biomaterial with tunable adhesive, elastic and degradation characteristics. As a first demonstration, we show that human mesenchymal stromal cells embedded in hydrogels and subjected to dynamic mechanical stimulation undergo myofibroblast differentiation. This system is readily scaled up to larger arrays, and will enable systematic and efficient screening of combinations of 3D mechanobiological and biomaterial cues on cell fate and function. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Nucleolar protein trafficking in response to HIV-1 Tat: rewiring the nucleolus.

PubMed

Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W; Gautier, Virginie W

2012-01-01

The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production.

Nucleolar Protein Trafficking in Response to HIV-1 Tat: Rewiring the Nucleolus

PubMed Central

Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W.; Gautier, Virginie W.

2012-01-01

The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production. PMID:23166591

A probabilistic cellular automata model for the dynamics of a population driven by logistic growth and weak Allee effect

NASA Astrophysics Data System (ADS)

Mendonça, J. R. G.

2018-04-01

We propose and investigate a one-parameter probabilistic mixture of one-dimensional elementary cellular automata under the guise of a model for the dynamics of a single-species unstructured population with nonoverlapping generations in which individuals have smaller probability of reproducing and surviving in a crowded neighbourhood but also suffer from isolation and dispersal. Remarkably, the first-order mean field approximation to the dynamics of the model yields a cubic map containing terms representing both logistic and weak Allee effects. The model has a single absorbing state devoid of individuals, but depending on the reproduction and survival probabilities can achieve a stable population. We determine the critical probability separating these two phases and find that the phase transition between them is in the directed percolation universality class of critical behaviour.

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Logic-based models in systems biology: a predictive and parameter-free network analysis method†

PubMed Central

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

Drug-induced cellular death dynamics monitored by a highly sensitive organic electrochemical system.

PubMed

Romeo, Agostino; Tarabella, Giuseppe; D'Angelo, Pasquale; Caffarra, Cristina; Cretella, Daniele; Alfieri, Roberta; Petronini, Pier Giorgio; Iannotta, Salvatore

2015-06-15

We propose and demonstrate a sensitive diagnostic device based on an Organic Electrochemical Transistor (OECT) for direct in-vitro monitoring cell death. The system efficiently monitors cell death dynamics, being able to detect signals related to specific death mechanisms, namely necrosis or early/late apoptosis, demonstrating a reproducible correlation between the OECT electrical response and the trends of standard cell death assays. The innovative design of the Twell-OECT system has been modeled to better correlate electrical signals with cell death dynamics. To qualify the device, we used a human lung adenocarcinoma cell line (A549) that was cultivated on the micro-porous membrane of a Transwell (Twell) support, and exposed to the anticancer drug doxorubicin. Time-dependent and dose-dependent dynamics of A549 cells exposed to doxorubicin are evaluated by monitoring cell death upon exposure to a range of doses and times that fully covers the protocols used in cancer treatment. The demonstrated ability to directly monitor cell stress and death dynamics upon drug exposure using simple electronic devices and, possibly, achieving selectivity to different cell dynamics is of great interest for several application fields, including toxicology, pharmacology, and therapeutics. Copyright © 2015 Elsevier B.V. All rights reserved.

Differentiation Driven Changes in the Dynamic Organization of Basal Transcription Initiation

PubMed Central

Giglia-Mari, Giuseppina; Mourgues, Sophie; Nonnekens, Julie; Andrieux, Lise O.; de Wit, Jan; Miquel, Catherine; Wijgers, Nils; Maas, Alex; Fousteri, Maria; Hoeijmakers, Jan H. J.; Vermeulen, Wim

2009-01-01

Studies based on cell-free systems and on in vitro–cultured living cells support the concept that many cellular processes, such as transcription initiation, are highly dynamic: individual proteins stochastically bind to their substrates and disassemble after reaction completion. This dynamic nature allows quick adaptation of transcription to changing conditions. However, it is unknown to what extent this dynamic transcription organization holds for postmitotic cells embedded in mammalian tissue. To allow analysis of transcription initiation dynamics directly into living mammalian tissues, we created a knock-in mouse model expressing fluorescently tagged TFIIH. Surprisingly and in contrast to what has been observed in cultured and proliferating cells, postmitotic murine cells embedded in their tissue exhibit a strong and long-lasting transcription-dependent immobilization of TFIIH. This immobilization is both differentiation driven and development dependent. Furthermore, although very statically bound, TFIIH can be remobilized to respond to new transcriptional needs. This divergent spatiotemporal transcriptional organization in different cells of the soma revisits the generally accepted highly dynamic concept of the kinetic framework of transcription and shows how basic processes, such as transcription, can be organized in a fundamentally different fashion in intact organisms as previously deduced from in vitro studies. PMID:19841728

Metascalable molecular dynamics simulation of nano-mechano-chemistry

NASA Astrophysics Data System (ADS)

Shimojo, F.; Kalia, R. K.; Nakano, A.; Nomura, K.; Vashishta, P.

2008-07-01

We have developed a metascalable (or 'design once, scale on new architectures') parallel application-development framework for first-principles based simulations of nano-mechano-chemical processes on emerging petaflops architectures based on spatiotemporal data locality principles. The framework consists of (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms, (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these scalable algorithms onto hardware. The EDC-STEP-HCD framework exposes and expresses maximal concurrency and data locality, thereby achieving parallel efficiency as high as 0.99 for 1.59-billion-atom reactive force field molecular dynamics (MD) and 17.7-million-atom (1.56 trillion electronic degrees of freedom) quantum mechanical (QM) MD in the framework of the density functional theory (DFT) on adaptive multigrids, in addition to 201-billion-atom nonreactive MD, on 196 608 IBM BlueGene/L processors. We have also used the framework for automated execution of adaptive hybrid DFT/MD simulation on a grid of six supercomputers in the US and Japan, in which the number of processors changed dynamically on demand and tasks were migrated according to unexpected faults. The paper presents the application of the framework to the study of nanoenergetic materials: (1) combustion of an Al/Fe2O3 thermite and (2) shock initiation and reactive nanojets at a void in an energetic crystal.

Side-binding proteins modulate actin filament dynamics

PubMed Central

Crevenna, Alvaro H; Arciniega, Marcelino; Dupont, Aurélie; Mizuno, Naoko; Kowalska, Kaja; Lange, Oliver F; Wedlich-Söldner, Roland; Lamb, Don C

2015-01-01

Actin filament dynamics govern many key physiological processes from cell motility to tissue morphogenesis. A central feature of actin dynamics is the capacity of filaments to polymerize and depolymerize at their ends in response to cellular conditions. It is currently thought that filament kinetics can be described by a single rate constant for each end. In this study, using direct visualization of single actin filament elongation, we show that actin polymerization kinetics at both filament ends are strongly influenced by the binding of proteins to the lateral filament surface. We also show that the pointed-end has a non-elongating state that dominates the observed filament kinetic asymmetry. Estimates of flexibility as well as effects on fragmentation and growth suggest that the observed kinetic diversity arises from structural alteration. Tuning elongation kinetics by exploiting the malleability of the filament structure may be a ubiquitous mechanism to generate a rich variety of cellular actin dynamics. DOI: http://dx.doi.org/10.7554/eLife.04599.001 PMID:25706231

Dynamics of ARF regulation that control senescence and cancer.

PubMed

Ko, Aram; Han, Su Yeon; Song, Jaewhan

2016-11-01

ARF is an alternative reading frame product of the INK4a/ARF locus, inactivated in numerous human cancers. ARF is a key regulator of cellular senescence, an irreversible cell growth arrest that suppresses tumor cell growth. It functions by sequestering MDM2 (a p53 E3 ligase) in the nucleolus, thus activating p53. Besides MDM2, ARF has numerous other interacting partners that induce either cellular senescence or apoptosis in a p53-independent manner. This further complicates the dynamics of the ARF network. Expression of ARF is frequently disrupted in human cancers, mainly due to epigenetic and transcriptional regulation. Vigorous studies on various transcription factors that either positively or negatively regulate ARF transcription have been carried out. However, recent focus on posttranslational modifications, particularly ubiquitination, indicates wider dynamic controls of ARF than previously known. In this review, we discuss the role and dynamic regulation of ARF in senescence and cancer. [BMB Reports 2016; 49(11): 598-606].

Collective Calcium Signaling of Defective Multicellular Networks

NASA Astrophysics Data System (ADS)

Potter, Garrett; Sun, Bo

2015-03-01

A communicating multicellular network processes environmental cues into collective cellular dynamics. We have previously demonstrated that, when excited by extracellular ATP, fibroblast monolayers generate correlated calcium dynamics modulated by both the stimuli and gap junction communication between the cells. However, just as a well-connected neural network may be compromised by abnormal neurons, a tissue monolayer can also be defective with cancer cells, which typically have down regulated gap junctions. To understand the collective cellular dynamics in a defective multicellular network we have studied the calcium signaling of co-cultured breast cancer cells and fibroblast cells in various concentrations of ATP delivered through microfluidic devices. Our results demonstrate that cancer cells respond faster, generate singular spikes, and are more synchronous across all stimuli concentrations. Additionally, fibroblast cells exhibit persistent calcium oscillations that increase in regularity with greater stimuli. To interpret these results we quantitatively analyzed the immunostaining of purigenic receptors and gap junction channels. The results confirm our hypothesis that collective dynamics are mainly determined by the availability of gap junction communications.

F-BAR family proteins, emerging regulators for cell membrane dynamic changes-from structure to human diseases.

PubMed

Liu, Suxuan; Xiong, Xinyu; Zhao, Xianxian; Yang, Xiaofeng; Wang, Hong

2015-05-09

Eukaryotic cell membrane dynamics change in curvature during physiological and pathological processes. In the past ten years, a novel protein family, Fes/CIP4 homology-Bin/Amphiphysin/Rvs (F-BAR) domain proteins, has been identified to be the most important coordinators in membrane curvature regulation. The F-BAR domain family is a member of the Bin/Amphiphysin/Rvs (BAR) domain superfamily that is associated with dynamic changes in cell membrane. However, the molecular basis in membrane structure regulation and the biological functions of F-BAR protein are unclear. The pathophysiological role of F-BAR protein is unknown. This review summarizes the current understanding of structure and function in the BAR domain superfamily, classifies F-BAR family proteins into nine subfamilies based on domain structure, and characterizes F-BAR protein structure, domain interaction, and functional relevance. In general, F-BAR protein binds to cell membrane via F-BAR domain association with membrane phospholipids and initiates membrane curvature and scission via Src homology-3 (SH3) domain interaction with its partner proteins. This process causes membrane dynamic changes and leads to seven important cellular biological functions, which include endocytosis, phagocytosis, filopodium, lamellipodium, cytokinesis, adhesion, and podosome formation, via distinct signaling pathways determined by specific domain-binding partners. These cellular functions play important roles in many physiological and pathophysiological processes. We further summarize F-BAR protein expression and mutation changes observed in various diseases and developmental disorders. Considering the structure feature and functional implication of F-BAR proteins, we anticipate that F-BAR proteins modulate physiological and pathophysiological processes via transferring extracellular materials, regulating cell trafficking and mobility, presenting antigens, mediating extracellular matrix degradation, and transmitting signaling for cell proliferation.

Resonance Raman Probes for Organelle-Specific Labeling in Live Cells

NASA Astrophysics Data System (ADS)

Kuzmin, Andrey N.; Pliss, Artem; Lim, Chang-Keun; Heo, Jeongyun; Kim, Sehoon; Rzhevskii, Alexander; Gu, Bobo; Yong, Ken-Tye; Wen, Shangchun; Prasad, Paras N.

2016-06-01

Raman microspectroscopy provides for high-resolution non-invasive molecular analysis of biological samples and has a breakthrough potential for dissection of cellular molecular composition at a single organelle level. However, the potential of Raman microspectroscopy can be fully realized only when novel types of molecular probes distinguishable in the Raman spectroscopy modality are developed for labeling of specific cellular domains to guide spectrochemical spatial imaging. Here we report on the design of a next generation Raman probe, based on BlackBerry Quencher 650 compound, which provides unprecedentedly high signal intensity through the Resonance Raman (RR) enhancement mechanism. Remarkably, RR enhancement occurs with low-toxic red light, which is close to maximum transparency in the biological optical window. The utility of proposed RR probes was validated for targeting lysosomes in live cultured cells, which enabled identification and subsequent monitoring of dynamic changes in this organelle by Raman imaging.

Nucleocytoplasmic transport in cells with progerin-induced defective nuclear lamina.

PubMed

Ferri, Gianmarco; Storti, Barbara; Bizzarri, Ranieri

2017-10-01

Recent data indicate that nuclear lamina (NL) plays a relevant role in many fundamental cellular functions. The peculiar role of NL in cells is dramatically demonstrated by the Hutchinson-Gilford progeria syndrome (HGPS), an inherited laminopathy that causes premature, rapid aging shortly after birth. In HGPS, a mutant form of Lamin A (progeria) leads to a dysmorphic NL structure, but how this perturbation is transduced into cellular changes is still largely unknown. Owing to the close structural relationship between NL and the Nuclear Pore Complex (NPC), in this work we test whether HGPS affects passive and active nucleo-cytoplasmic shuttling of cargoes by means of an established model based of fluorescence recovery after photobleaching. Our findings clearly demonstrate that dysmorphic NL is decoupled from the dynamic characteristics of passive and active transport towards and from the nucleus, as well as from the binding affinity of transport protein mediators. Copyright © 2017 Elsevier B.V. All rights reserved.

Calcium neuroimaging in behaving zebrafish larvae using a turn-key light field camera

NASA Astrophysics Data System (ADS)

Cruz Perez, Carlos; Lauri, Antonella; Symvoulidis, Panagiotis; Cappetta, Michele; Erdmann, Arne; Westmeyer, Gil Gregor

2015-09-01

Reconstructing a three-dimensional scene from multiple simultaneously acquired perspectives (the light field) is an elegant scanless imaging concept that can exceed the temporal resolution of currently available scanning-based imaging methods for capturing fast cellular processes. We tested the performance of commercially available light field cameras on a fluorescent microscopy setup for monitoring calcium activity in the brain of awake and behaving reporter zebrafish larvae. The plenoptic imaging system could volumetrically resolve diverse neuronal response profiles throughout the zebrafish brain upon stimulation with an aversive odorant. Behavioral responses of the reporter fish could be captured simultaneously together with depth-resolved neuronal activity. Overall, our assessment showed that with some optimizations for fluorescence microscopy applications, commercial light field cameras have the potential of becoming an attractive alternative to custom-built systems to accelerate molecular imaging research on cellular dynamics.

Calcium neuroimaging in behaving zebrafish larvae using a turn-key light field camera.

PubMed

Perez, Carlos Cruz; Lauri, Antonella; Symvoulidis, Panagiotis; Cappetta, Michele; Erdmann, Arne; Westmeyer, Gil Gregor

2015-09-01

Reconstructing a three-dimensional scene from multiple simultaneously acquired perspectives (the light field) is an elegant scanless imaging concept that can exceed the temporal resolution of currently available scanning-based imaging methods for capturing fast cellular processes. We tested the performance of commercially available light field cameras on a fluorescent microscopy setup for monitoring calcium activity in the brain of awake and behaving reporter zebrafish larvae. The plenoptic imaging system could volumetrically resolve diverse neuronal response profiles throughout the zebrafish brain upon stimulation with an aversive odorant. Behavioral responses of the reporter fish could be captured simultaneously together with depth-resolved neuronal activity. Overall, our assessment showed that with some optimizations for fluorescence microscopy applications, commercial light field cameras have the potential of becoming an attractive alternative to custom-built systems to accelerate molecular imaging research on cellular dynamics.

Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources.

PubMed

Nev, Olga A; van den Berg, Hugo A

2017-01-01

Variable-Internal-Stores models of microbial metabolism and growth have proven to be invaluable in accounting for changes in cellular composition as microbial cells adapt to varying conditions of nutrient availability. Here, such a model is extended with explicit allocation of molecular building blocks among various types of catalytic machinery. Such an extension allows a reconstruction of the regulatory rules employed by the cell as it adapts its physiology to changing environmental conditions. Moreover, the extension proposed here creates a link between classic models of microbial growth and analyses based on detailed transcriptomics and proteomics data sets. We ascertain the compatibility between the extended Variable-Internal-Stores model and the classic models, demonstrate its behaviour by means of simulations, and provide a detailed treatment of the uniqueness and the stability of its equilibrium point as a function of the availabilities of the various nutrients.

Membrane rupture generates single open membrane sheets during vaccinia virus assembly.

PubMed

Chlanda, Petr; Carbajal, Maria Alejandra; Cyrklaff, Marek; Griffiths, Gareth; Krijnse-Locker, Jacomine

2009-07-23

The biogenesis and dynamics of cellular membranes are governed by fusion and fission processes that ensure the maintenance of closed compartments. These principles also apply to viruses during acquisition of their envelope. Based on conventional electron microscopy (EM), however, it has been proposed that poxviruses assemble from membranes made de novo with "free" ends in the cytoplasm. Here, we analyze the origin and structure of poxvirus membranes in a close-to-native state and in three dimensions by using cryopreservation and electron tomography (ET). By cryo-EM, the precursor membrane of poxviruses appears as an open membrane sheet stabilized by a protein scaffold. ET shows that this membrane is derived from pre-existing cellular membranes that rupture to generate an open compartment, rather than being made de novo. Thus, poxvirus infection represents an excellent system to study how cytoplasmic membranes can form open sheets by a process distinct from well-defined mechanisms of membrane biogenesis.

Multi-classification of cell deformation based on object alignment and run length statistic.

PubMed

Li, Heng; Liu, Zhiwen; An, Xing; Shi, Yonggang

2014-01-01

Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.

Anomalous transport in cellular flows: The role of initial conditions and aging

NASA Astrophysics Data System (ADS)

Pöschke, Patrick; Sokolov, Igor M.; Nepomnyashchy, Alexander A.; Zaks, Michael A.

2016-09-01

We consider the diffusion-advection problem in two simple cellular flow models (often invoked as examples of subdiffusive tracer motion) and concentrate on the intermediate time range, in which the tracer motion indeed may show subdiffusion. We perform extensive numerical simulations of the systems under different initial conditions and show that the pure intermediate-time subdiffusion regime is only evident when the particles start at the border between different cells, i.e., at the separatrix, and is less pronounced or absent for other initial conditions. The motion moreover shows quite peculiar aging properties, which are also mirrored in the behavior of the time-averaged mean squared displacement for single trajectories. This kind of behavior is due to the complex motion of tracers trapped inside the cell and is absent in classical models based on continuous-time random walks with no dynamics in the trapped state.

Fluorogenic RNA Mango aptamers for imaging small non-coding RNAs in mammalian cells.

PubMed

Autour, Alexis; C Y Jeng, Sunny; D Cawte, Adam; Abdolahzadeh, Amir; Galli, Angela; Panchapakesan, Shanker S S; Rueda, David; Ryckelynck, Michael; Unrau, Peter J

2018-02-13

Despite having many key roles in cellular biology, directly imaging biologically important RNAs has been hindered by a lack of fluorescent tools equivalent to the fluorescent proteins available to study cellular proteins. Ideal RNA labelling systems must preserve biological function, have photophysical properties similar to existing fluorescent proteins, and be compatible with established live and fixed cell protein labelling strategies. Here, we report a microfluidics-based selection of three new high-affinity RNA Mango fluorogenic aptamers. Two of these are as bright or brighter than enhanced GFP when bound to TO1-Biotin. Furthermore, we show that the new Mangos can accurately image the subcellular localization of three small non-coding RNAs (5S, U6, and a box C/D scaRNA) in fixed and live mammalian cells. These new aptamers have many potential applications to study RNA function and dynamics both in vitro and in mammalian cells.

Enhanced Communication Network Solution for Positive Train Control Implementation

NASA Technical Reports Server (NTRS)

Fatehi, M. T.; Simon, J.; Chang, W.; Chow, E. T.; Burleigh, S. C.

2011-01-01

The commuter and freight railroad industry is required to implement Positive Train Control (PTC) by 2015 (2012 for Metrolink), a challenging network communications problem. This paper will discuss present technologies developed by the National Aeronautics and Space Administration (NASA) to overcome comparable communication challenges encountered in deep space mission operations. PTC will be based on a new cellular wireless packet Internet Protocol (IP) network. However, ensuring reliability in such a network is difficult due to the "dead zones" and transient disruptions we commonly experience when we lose calls in commercial cellular networks. These disruptions make it difficult to meet PTC s stringent reliability (99.999%) and safety requirements, deployment deadlines, and budget. This paper proposes innovative solutions based on space-proven technologies that would help meet these challenges: (1) Delay Tolerant Networking (DTN) technology, designed for use in resource-constrained, embedded systems and currently in use on the International Space Station, enables reliable communication over networks in which timely data acknowledgments might not be possible due to transient link outages. (2) Policy-Based Management (PBM) provides dynamic management capabilities, allowing vital data to be exchanged selectively (with priority) by utilizing alternative communication resources. The resulting network may help railroads implement PTC faster, cheaper, and more reliably.

Biodynsensing: Sensing Through Dynamics of Hybrid Affinity/Cellular Platforms; Towards Appraisal of Environmental and Biological Risks of Nanobiotechnology

NASA Astrophysics Data System (ADS)

Gheorghiu, E.; Gheorghiu, M.; David, S.; Polonschii, C.

Chemical cues and nano-topographies present on the surface or in the extracellular medium strongly influence the fate and adhesion of biological cells. Careful tuning of cell—matrix interaction via engineered surfaces, either attractive or repulsive, require non-invasive, long time monitoring capabilities and lay the foundation of sensing platforms for risk assessment. Aiming to assess changes underwent by biointerfaces due to cell—environment interaction (in particular nanotechnology products), we have developed hybrid cellular platforms allowing for time based dual assays, i.e., impedance/dielectric spectroscopy (IS) and Surface Plasmon Resonance (SPR). Such platforms comprising Flow Injection Analysis (FIA) have been advanced to assess the interaction between selected (normal and malignant) cells and nano-patterned and/or chemically modified surfaces, as well as the impact of engineered nanoparticles, revealed by the related changes exhibited by cell membrane, morphology, adhesion and monolayer integrity. Besides experimental aspects dealing with measurement set-up, we will emphasize theoretical aspects related to: dielectric modeling. Aiming for a quantitative approach, microscopic models on dielectric behavior of ensembles of interconnected cells have been developed and their capabilities will be outlined within the presentation. Assessment of affinity reactions as revealed by dielectric/impedance assays of biointerfaces. Modeling the dynamics of the impedance in relation to the “quality” of cell layer and sensor's active surface, this study presents further developments of our approach described in Analytical Chemistry, 2002. Data analysis. This issue is related to the following basic question: Are there “simple” Biosensing Platforms? When coping with cellular platforms, either in suspension or immobilized (on filters, adhered on surfaces or entrapped, e.g., on using set-ups) there is an intrinsic nonlinear behavior of biological systems related to cellular mechanisms involved in sensing, i.e., adaptation to stimuli. This should not mean that when coping with living cells, stray effects might not also corrupt the measurement itself, introducing distinct dynamics. Besides targeted/specific process, analytical platforms might exhibit additional ones due to “stray influences” that could include the effect of, e.g.: supporting matrix, nonspecific binding and temperature variation. Stray processes interfere with the desired ones and the measured data could display a non-monotonous behavior.

Interference of mobile phones and digitally enhanced cordless telecommunications mobile phones in renal scintigraphy.

PubMed

Stegmayr, Armin; Fessl, Benjamin; Hörtnagl, Richard; Marcadella, Michael; Perkhofer, Susanne

2013-08-01

The aim of the study was to assess the potential negative impact of cellular phones and digitally enhanced cordless telecommunication (DECT) devices on the quality of static and dynamic scintigraphy to avoid repeated testing in infant and teenage patients to protect them from unnecessary radiation exposure. The assessment was conducted by performing phantom measurements under real conditions. A functional renal-phantom acting as a pair of kidneys in dynamic scans was created. Data were collected using the setup of cellular phones and DECT phones placed in different positions in relation to a camera head to test the potential interference of cellular phones and DECT phones with the cameras. Cellular phones reproducibly interfered with the oldest type of gamma camera, which, because of its single-head specification, is the device most often used for renal examinations. Curves indicating the renal function were considerably disrupted; cellular phones as well as DECT phones showed a disturbance concerning static acquisition. Variable electromagnetic tolerance in different types of γ-cameras could be identified. Moreover, a straightforward, low-cost method of testing the susceptibility of equipment to interference caused by cellular phones and DECT phones was generated. Even though some departments use newer models of γ-cameras, which are less susceptible to electromagnetic interference, we recommend testing examination rooms to avoid any interference caused by cellular phones. The potential electromagnetic interference should be taken into account when the purchase of new sensitive medical equipment is being considered, not least because the technology of mobile communication is developing fast, which also means that different standards of wave bands will be issued in the future.

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

PubMed

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models.

Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

PubMed Central

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models. PMID:24244124

Cell Patterns Emerge from Coupled Chemical and Physical Fields with Cell Proliferation Dynamics: The Arabidopsis thaliana Root as a Study System

PubMed Central

Barrio, Rafael A.; Romero-Arias, José Roberto; Noguez, Marco A.; Azpeitia, Eugenio; Ortiz-Gutiérrez, Elizabeth; Hernández-Hernández, Valeria; Cortes-Poza, Yuriria; Álvarez-Buylla, Elena R.

2013-01-01

A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems. PMID:23658505

Searching target sites on DNA by proteins: Role of DNA dynamics under confinement

PubMed Central

Mondal, Anupam; Bhattacherjee, Arnab

2015-01-01

DNA-binding proteins (DBPs) rapidly search and specifically bind to their target sites on genomic DNA in order to trigger many cellular regulatory processes. It has been suggested that the facilitation of search dynamics is achieved by combining 3D diffusion with one-dimensional sliding and hopping dynamics of interacting proteins. Although, recent studies have advanced the knowledge of molecular determinants that affect one-dimensional search efficiency, the role of DNA molecule is poorly understood. In this study, by using coarse-grained simulations, we propose that dynamics of DNA molecule and its degree of confinement due to cellular crowding concertedly regulate its groove geometry and modulate the inter-communication with DBPs. Under weak confinement, DNA dynamics promotes many short, rotation-decoupled sliding events interspersed by hopping dynamics. While this results in faster 1D diffusion, associated probability of missing targets by jumping over them increases. In contrast, strong confinement favours rotation-coupled sliding to locate targets but lacks structural flexibility to achieve desired specificity. By testing under physiological crowding, our study provides a plausible mechanism on how DNA molecule may help in maintaining an optimal balance between fast hopping and rotation-coupled sliding dynamics, to locate target sites rapidly and form specific complexes precisely. PMID:26400158

Axon Regeneration in C. elegans

PubMed Central

Hammarlund, Marc; Jin, Yishi

2014-01-01

Single axon transection by laser surgery has made C. elegans a new model for axon regeneration. Multiple conserved molecular signaling modules have been discovered through powerful genetic screening. in vivo imaging with single cell and axon resolution has revealed unprecedented cellular dynamics in regenerating axons. Information from C. elegans has greatly expanded our knowledge of the molecular and cellular mechanisms of axon regeneration. PMID:24794753

A cellular automaton implementation of a quantum battle of the sexes game with imperfect information

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

2015-10-01

The dynamics of a spatial quantum formulation of the iterated battle of the sexes game with imperfect information is studied in this work. The game is played with variable entangling in a cellular automata manner, i.e. with local and synchronous interaction. The effect of spatial structure is assessed in fair and unfair scenarios.

Cellular Spacing Selection During the Directional Solidification of Binary Alloys. A Numerical Approach

NASA Technical Reports Server (NTRS)

Catalina, Adrian V.; Sen, S.; Rose, M. Franklin (Technical Monitor)

2001-01-01

The evolution of cellular solid/liquid interfaces from an initially unstable planar front was studied by means of a two-dimensional computer simulation. The developed numerical model makes use of an interface tracking procedure and has the capability to describe the dynamics of the interface morphology based on local changes of the thermodynamic conditions. The fundamental physics of this formulation was validated against experimental microgravity results and the predictions of the analytical linear stability theory. The performed simulations revealed that in certain conditions, based on a competitive growth mechanism, an interface could become unstable to random perturbations of infinitesimal amplitude even at wavelengths smaller than the neutral wavelength, lambda(sub c), predicted by the linear stability theory. Furthermore, two main stages of spacing selection have been identified. In the first stage, at low perturbations amplitude, the selection mechanism is driven by the maximum growth rate of instabilities while in the second stage the selection is influenced by nonlinear phenomena caused by the interactions between the neighboring cells. Comparison of these predictions with other existing theories of pattern formation and experimental results will be discussed.