Sample records for single cell network

  1. Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.

    PubMed

    Chen, Shuonan; Mar, Jessica C

    2018-06-19

    A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. Meanwhile, although methods that are specific for single cell data are now emerging, whether they have improved performance over general methods is unknown. In this study, we evaluate the applicability of five general methods and three single cell methods for inferring gene regulatory networks from both experimental single cell gene expression data and in silico simulated data. Standard evaluation metrics using ROC curves and Precision-Recall curves against reference sets sourced from the literature demonstrated that most of the methods performed poorly when they were applied to either experimental single cell data, or simulated single cell data, which demonstrates their lack of performance for this task. Using default settings, network methods were applied to the same datasets. Comparisons of the learned networks highlighted the uniqueness of some predicted edges for each method. The fact that different methods infer networks that vary substantially reflects the underlying mathematical rationale and assumptions that distinguish network methods from each other. This study provides a comprehensive evaluation of network modeling algorithms applied to experimental single cell gene expression data and in silico simulated datasets where the network structure is known. Comparisons demonstrate that most of these assessed network methods are not able to predict network structures from single cell expression data accurately, even if they are specifically developed for single cell methods. Also, single cell methods, which usually depend on more elaborative algorithms, in general have less similarity to each other in the sets of edges detected. The results from this study emphasize the importance for developing more accurate optimized network modeling methods that are compatible for single cell data. Newly-developed single cell methods may uniquely capture particular features of potential gene-gene relationships, and caution should be taken when we interpret these results.

  2. Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements

    PubMed Central

    Haghverdi, Laleh; Lilly, Andrew J.; Tanaka, Yosuke; Wilkinson, Adam C.; Buettner, Florian; Macaulay, Iain C.; Jawaid, Wajid; Diamanti, Evangelia; Nishikawa, Shin-Ichi; Piterman, Nir; Kouskoff, Valerie; Theis, Fabian J.; Fisher, Jasmin; Göttgens, Berthold

    2015-01-01

    Here we report the use of diffusion maps and network synthesis from state transition graphs to better understand developmental pathways from single cell gene expression profiling. We map the progression of mesoderm towards blood in the mouse by single-cell expression analysis of 3,934 cells, capturing cells with blood-forming potential at four sequential developmental stages. By adapting the diffusion plot methodology for dimensionality reduction to single-cell data, we reconstruct the developmental journey to blood at single-cell resolution. Using transitions between individual cellular states as input, we develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model that recapitulates blood development. Model predictions were validated by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that control organogenesis. PMID:25664528

  3. A nanobiosensor for dynamic single cell analysis during microvascular self-organization.

    PubMed

    Wang, S; Sun, J; Zhang, D D; Wong, P K

    2016-10-14

    The formation of microvascular networks plays essential roles in regenerative medicine and tissue engineering. Nevertheless, the self-organization mechanisms underlying the dynamic morphogenic process are poorly understood due to a paucity of effective tools for mapping the spatiotemporal dynamics of single cell behaviors. By establishing a single cell nanobiosensor along with live cell imaging, we perform dynamic single cell analysis of the morphology, displacement, and gene expression during microvascular self-organization. Dynamic single cell analysis reveals that endothelial cells self-organize into subpopulations with specialized phenotypes to form microvascular networks and identifies the involvement of Notch1-Dll4 signaling in regulating the cell subpopulations. The cell phenotype correlates with the initial Dll4 mRNA expression level and each subpopulation displays a unique dynamic Dll4 mRNA expression profile. Pharmacological perturbations and RNA interference of Notch1-Dll4 signaling modulate the cell subpopulations and modify the morphology of the microvascular network. Taken together, a nanobiosensor enables a dynamic single cell analysis approach underscoring the importance of Notch1-Dll4 signaling in microvascular self-organization.

  4. Fundamental trade-offs between information flow in single cells and cellular populations.

    PubMed

    Suderman, Ryan; Bachman, John A; Smith, Adam; Sorger, Peter K; Deeds, Eric J

    2017-05-30

    Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

  5. Cell-cell bioelectrical interactions and local heterogeneities in genetic networks: a model for the stabilization of single-cell states and multicellular oscillations.

    PubMed

    Cervera, Javier; Manzanares, José A; Mafe, Salvador

    2018-04-04

    Genetic networks operate in the presence of local heterogeneities in single-cell transcription and translation rates. Bioelectrical networks and spatio-temporal maps of cell electric potentials can influence multicellular ensembles. Could cell-cell bioelectrical interactions mediated by intercellular gap junctions contribute to the stabilization of multicellular states against local genetic heterogeneities? We theoretically analyze this question on the basis of two well-established experimental facts: (i) the membrane potential is a reliable read-out of the single-cell electrical state and (ii) when the cells are coupled together, their individual cell potentials can be influenced by ensemble-averaged electrical potentials. We propose a minimal biophysical model for the coupling between genetic and bioelectrical networks that associates the local changes occurring in the transcription and translation rates of an ion channel protein with abnormally low (depolarized) cell potentials. We then analyze the conditions under which the depolarization of a small region (patch) in a multicellular ensemble can be reverted by its bioelectrical coupling with the (normally polarized) neighboring cells. We show also that the coupling between genetic and bioelectric networks of non-excitable cells, modulated by average electric potentials at the multicellular ensemble level, can produce oscillatory phenomena. The simulations show the importance of single-cell potentials characteristic of polarized and depolarized states, the relative sizes of the abnormally polarized patch and the rest of the normally polarized ensemble, and intercellular coupling.

  6. Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

    PubMed

    Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

    2017-12-28

    Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate networks. The research results in this work shows that the developed approach is an efficient and effective method to reverse-engineer gene networks using single-cell experimental observations.

  7. Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa.

    PubMed

    Caranica, C; Al-Omari, A; Deng, Z; Griffith, J; Nilsen, R; Mao, L; Arnold, J; Schüttler, H-B

    2018-01-01

    A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data. The method is relatively fast (compared to Metropolis-Hastings Monte Carlo Methods), easy to parallelize, applicable to large oscillatory networks and large (~2000 cells) single cell expression data sets, and it quantifies the noise impact on the observed dynamics. Standard errors of estimated rate coefficients are typically two orders of magnitude smaller than the mean from single cell experiments with on the order of ~1000 cells. We also provide a method to assess the goodness of fit of the stochastic network using the Hilbert phase of single cells. An analysis of phase departures from the null model with no communication between cells is consistent with a hypothesis of Stochastic Resonance describing single cell oscillators. Stochastic Resonance provides a physical mechanism whereby intracellular noise plays a positive role in establishing oscillatory behavior, but may require model parameters, such as rate coefficients, that differ substantially from those extracted at the macroscopic level from measurements on populations of millions of communicating, synchronized cells.

  8. Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters

    NASA Astrophysics Data System (ADS)

    Munsky, Brian; Trinh, Brooke; Khammash, Mustafa

    2010-03-01

    The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.

  9. TRACING CO-REGULATORY NETWORK DYNAMICS IN NOISY, SINGLE-CELL TRANSCRIPTOME TRAJECTORIES.

    PubMed

    Cordero, Pablo; Stuart, Joshua M

    2017-01-01

    The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression 'trajectory' from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves. SCIMITAR yields rich models from the data that highlight genes with expression and co-expression patterns that are associated with the inferred progression. Further, SCIMITAR extracts regulatory states from the implicated trajectory-evolvingco-expression networks. We benchmark the method on simulated data to show that it yields accurate cell ordering and gene network inferences. Applied to the interpretation of a single-cell human fetal neuron dataset, SCIMITAR finds progression-associated genes in cornerstone neural differentiation pathways missed by standard differential expression tests. Finally, by leveraging the rewiring of gene-gene co-expression relations across the progression, the method reveals the rise and fall of co-regulatory states and trajectory-dependent gene modules. These analyses implicate new transcription factors in neural differentiation including putative co-factors for the multi-functional NFAT pathway.

  10. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    PubMed Central

    Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

    2018-01-01

    The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

  11. SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

    PubMed

    Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

    2018-05-25

    Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

  12. Geometry and network connectivity govern the mechanics of stress fibers.

    PubMed

    Kassianidou, Elena; Brand, Christoph A; Schwarz, Ulrich S; Kumar, Sanjay

    2017-03-07

    Actomyosin stress fibers (SFs) play key roles in driving polarized motility and generating traction forces, yet little is known about how tension borne by an individual SF is governed by SF geometry and its connectivity to other cytoskeletal elements. We now address this question by combining single-cell micropatterning with subcellular laser ablation to probe the mechanics of single, geometrically defined SFs. The retraction length of geometrically isolated SFs after cutting depends strongly on SF length, demonstrating that longer SFs dissipate more energy upon incision. Furthermore, when cell geometry and adhesive spacing are fixed, cell-to-cell heterogeneities in SF dissipated elastic energy can be predicted from varying degrees of physical integration with the surrounding network. We apply genetic, pharmacological, and computational approaches to demonstrate a causal and quantitative relationship between SF connectivity and mechanics for patterned cells and show that similar relationships hold for nonpatterned cells allowed to form cell-cell contacts in monolayer culture. Remarkably, dissipation of a single SF within a monolayer induces cytoskeletal rearrangements in cells long distances away. Finally, stimulation of cell migration leads to characteristic changes in network connectivity that promote SF bundling at the cell rear. Our findings demonstrate that SFs influence and are influenced by the networks in which they reside. Such higher order network interactions contribute in unexpected ways to cell mechanics and motility.

  13. Advanced Ring-Shaped Microelectrode Assay Combined with Small Rectangular Electrode for Quasi-In vivo Measurement of Cell-to-Cell Conductance in Cardiomyocyte Network

    NASA Astrophysics Data System (ADS)

    Nomura, Fumimasa; Kaneko, Tomoyuki; Hamada, Tomoyo; Hattori, Akihiro; Yasuda, Kenji

    2013-06-01

    To predict the risk of fatal arrhythmia induced by cardiotoxicity in the highly complex human heart system, we have developed a novel quasi-in vivo electrophysiological measurement assay, which combines a ring-shaped human cardiomyocyte network and a set of two electrodes that form a large single ring-shaped electrode for the direct measurement of irregular cell-to-cell conductance occurrence in a cardiomyocyte network, and a small rectangular microelectrode for forced pacing of cardiomyocyte beating and for acquiring the field potential waveforms of cardiomyocytes. The advantages of this assay are as follows. The electrophysiological signals of cardiomyocytes in the ring-shaped network are superimposed directly on a single loop-shaped electrode, in which the information of asynchronous behavior of cell-to-cell conductance are included, without requiring a set of huge numbers of microelectrode arrays, a set of fast data conversion circuits, or a complex analysis in a computer. Another advantage is that the small rectangular electrode can control the position and timing of forced beating in a ring-shaped human induced pluripotent stem cell (hiPS)-derived cardiomyocyte network and can also acquire the field potentials of cardiomyocytes. First, we constructed the human iPS-derived cardiomyocyte ring-shaped network on the set of two electrodes, and acquired the field potential signals of particular cardiomyocytes in the ring-shaped cardiomyocyte network during simultaneous acquisition of the superimposed signals of whole-cardiomyocyte networks representing cell-to-cell conduction. Using the small rectangular electrode, we have also evaluated the response of the cell network to electrical stimulation. The mean and SD of the minimum stimulation voltage required for pacing (VMin) at the small rectangular electrode was 166+/-74 mV, which is the same as the magnitude of amplitude for the pacing using the ring-shaped electrode (179+/-33 mV). The results showed that the addition of a small rectangular electrode into the ring-shaped electrode was effective for the simultaneous measurement of whole-cell-network signals and single-cell/small-cluster signals on a local site in the cell network, and for the pacing by electrical stimulation of cardiomyocyte networks.

  14. Geometry and network connectivity govern the mechanics of stress fibers

    PubMed Central

    Kassianidou, Elena; Brand, Christoph A.; Kumar, Sanjay

    2017-01-01

    Actomyosin stress fibers (SFs) play key roles in driving polarized motility and generating traction forces, yet little is known about how tension borne by an individual SF is governed by SF geometry and its connectivity to other cytoskeletal elements. We now address this question by combining single-cell micropatterning with subcellular laser ablation to probe the mechanics of single, geometrically defined SFs. The retraction length of geometrically isolated SFs after cutting depends strongly on SF length, demonstrating that longer SFs dissipate more energy upon incision. Furthermore, when cell geometry and adhesive spacing are fixed, cell-to-cell heterogeneities in SF dissipated elastic energy can be predicted from varying degrees of physical integration with the surrounding network. We apply genetic, pharmacological, and computational approaches to demonstrate a causal and quantitative relationship between SF connectivity and mechanics for patterned cells and show that similar relationships hold for nonpatterned cells allowed to form cell–cell contacts in monolayer culture. Remarkably, dissipation of a single SF within a monolayer induces cytoskeletal rearrangements in cells long distances away. Finally, stimulation of cell migration leads to characteristic changes in network connectivity that promote SF bundling at the cell rear. Our findings demonstrate that SFs influence and are influenced by the networks in which they reside. Such higher order network interactions contribute in unexpected ways to cell mechanics and motility. PMID:28213499

  15. Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states

    PubMed Central

    Jang, Sumin; Choubey, Sandeep; Furchtgott, Leon; Zou, Ling-Nan; Doyle, Adele; Menon, Vilas; Loew, Ethan B; Krostag, Anne-Rachel; Martinez, Refugio A; Madisen, Linda; Levi, Boaz P; Ramanathan, Sharad

    2017-01-01

    The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.001 PMID:28296635

  16. Multi-level characterization of balanced inhibitory-excitatory cortical neuron network derived from human pluripotent stem cells.

    PubMed

    Nadadhur, Aishwarya G; Emperador Melero, Javier; Meijer, Marieke; Schut, Desiree; Jacobs, Gerbren; Li, Ka Wan; Hjorth, J J Johannes; Meredith, Rhiannon M; Toonen, Ruud F; Van Kesteren, Ronald E; Smit, August B; Verhage, Matthijs; Heine, Vivi M

    2017-01-01

    Generation of neuronal cultures from induced pluripotent stem cells (hiPSCs) serve the studies of human brain disorders. However we lack neuronal networks with balanced excitatory-inhibitory activities, which are suitable for single cell analysis. We generated low-density networks of hPSC-derived GABAergic and glutamatergic cortical neurons. We used two different co-culture models with astrocytes. We show that these cultures have balanced excitatory-inhibitory synaptic identities using confocal microscopy, electrophysiological recordings, calcium imaging and mRNA analysis. These simple and robust protocols offer the opportunity for single-cell to multi-level analysis of patient hiPSC-derived cortical excitatory-inhibitory networks; thereby creating advanced tools to study disease mechanisms underlying neurodevelopmental disorders.

  17. A modular network for legged locomotion

    NASA Astrophysics Data System (ADS)

    Golubitsky, Martin; Stewart, Ian; Buono, Pietro-Luciano; Collins, J. J.

    1998-04-01

    In this paper we use symmetry methods to study networks of coupled cells, which are models for central pattern generators (CPGs). In these models the cells obey identical systems of differential equations and the network specifies how cells are coupled. Previously, Collins and Stewart showed that the phase relations of many of the standard gaits of quadrupeds and hexapods can be obtained naturally via Hopf bifurcation in small networks. For example, the networks they used to study quadrupeds all had four cells, with the understanding that each cell determined the phase of the motion of one leg. However, in their work it seemed necessary to employ several different four-oscillator networks to obtain all of the standard quadrupedal gaits. We show that this difficulty with four-oscillator networks is unavoidable, but that the problems can be overcome by using a larger network. Specifically, we show that the standard gaits of a quadruped, including walk, trot and pace, cannot all be realized by a single four-cell network without introducing unwanted conjugacies between trot and pace - conjugacies that imply a dynamic equivalence between these gaits that seems inconsistent with observations. In this sense a single network with four cells cannot model the CPG of a quadruped. We also introduce a single eight-cell network that can model all of the primary gaits of quadrupeds without these unwanted conjugacies. Moreover, this network is modular in that it naturally generalizes to provide models of gaits in hexapods, centipedes, and millipedes. The analysis of models for many-legged animals shows that wave-like motions, similar to those obtained by Kopell and Ermentrout, can be expected. However, our network leads to a prediction that the wavelength of the wave motion will divide twice the length of the animal. Indeed, we reproduce illustrations of wave-like motions in centipedes where the animal is approximately one-and-a-half wavelength long - motions that are consistent with this prediction. We discuss the implications of these results for the development of modular control networks for adaptive legged robots.

  18. Clustering Single-Cell Expression Data Using Random Forest Graphs.

    PubMed

    Pouyan, Maziyar Baran; Nourani, Mehrdad

    2017-07-01

    Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

  19. Sparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time Series.

    PubMed

    Klimovskaia, Anna; Ganscha, Stefan; Claassen, Manfred

    2016-12-01

    Stochastic chemical reaction networks constitute a model class to quantitatively describe dynamics and cell-to-cell variability in biological systems. The topology of these networks typically is only partially characterized due to experimental limitations. Current approaches for refining network topology are based on the explicit enumeration of alternative topologies and are therefore restricted to small problem instances with almost complete knowledge. We propose the reactionet lasso, a computational procedure that derives a stepwise sparse regression approach on the basis of the Chemical Master Equation, enabling large-scale structure learning for reaction networks by implicitly accounting for billions of topology variants. We have assessed the structure learning capabilities of the reactionet lasso on synthetic data for the complete TRAIL induced apoptosis signaling cascade comprising 70 reactions. We find that the reactionet lasso is able to efficiently recover the structure of these reaction systems, ab initio, with high sensitivity and specificity. With only < 1% false discoveries, the reactionet lasso is able to recover 45% of all true reactions ab initio among > 6000 possible reactions and over 102000 network topologies. In conjunction with information rich single cell technologies such as single cell RNA sequencing or mass cytometry, the reactionet lasso will enable large-scale structure learning, particularly in areas with partial network structure knowledge, such as cancer biology, and thereby enable the detection of pathological alterations of reaction networks. We provide software to allow for wide applicability of the reactionet lasso.

  20. Reconstructing blood stem cell regulatory network models from single-cell molecular profiles

    PubMed Central

    Hamey, Fiona K.; Nestorowa, Sonia; Kinston, Sarah J.; Kent, David G.; Wilson, Nicola K.

    2017-01-01

    Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships. PMID:28584094

  1. Transcriptional Networks in Single Perivascular Cells Sorted from Human Adipose Tissue Reveal a Hierarchy of Mesenchymal Stem Cells.

    PubMed

    Hardy, W Reef; Moldovan, Nicanor I; Moldovan, Leni; Livak, Kenneth J; Datta, Krishna; Goswami, Chirayu; Corselli, Mirko; Traktuev, Dmitry O; Murray, Iain R; Péault, Bruno; March, Keith

    2017-05-01

    Adipose tissue is a rich source of multipotent mesenchymal stem-like cells, located in the perivascular niche. Based on their surface markers, these have been assigned to two main categories: CD31 - /CD45 - /CD34 + /CD146 - cells (adventitial stromal/stem cells [ASCs]) and CD31 - /CD45 - /CD34 - /CD146 + cells (pericytes [PCs]). These populations display heterogeneity of unknown significance. We hypothesized that aldehyde dehydrogenase (ALDH) activity, a functional marker of primitivity, could help to better define ASC and PC subclasses. To this end, the stromal vascular fraction from a human lipoaspirate was simultaneously stained with fluorescent antibodies to CD31, CD45, CD34, and CD146 antigens and the ALDH substrate Aldefluor, then sorted by fluorescence-activated cell sorting. Individual ASCs (n = 67) and PCs (n = 73) selected from the extremities of the ALDH-staining spectrum were transcriptionally profiled by Fluidigm single-cell quantitative polymerase chain reaction for a predefined set (n = 429) of marker genes. To these single-cell data, we applied differential expression and principal component and clustering analysis, as well as an original gene coexpression network reconstruction algorithm. Despite the stochasticity at the single-cell level, covariation of gene expression analysis yielded multiple network connectivity parameters suggesting that these perivascular progenitor cell subclasses possess the following order of maturity: (a) ALDH br ASC (most primitive); (b) ALDH dim ASC; (c) ALDH br PC; (d) ALDH dim PC (least primitive). This order was independently supported by specific combinations of class-specific expressed genes and further confirmed by the analysis of associated signaling pathways. In conclusion, single-cell transcriptional analysis of four populations isolated from fat by surface markers and enzyme activity suggests a developmental hierarchy among perivascular mesenchymal stem cells supported by markers and coexpression networks. Stem Cells 2017;35:1273-1289. © 2017 AlphaMed Press.

  2. Localized electrical stimulation of in vitro neurons using an array of sub-cellular sized electrodes.

    PubMed

    Braeken, Dries; Huys, Roeland; Loo, Josine; Bartic, Carmen; Borghs, Gustaaf; Callewaert, Geert; Eberle, Wolfgang

    2010-12-15

    The investigation of single-neuron parameters is of great interest because many aspects in the behavior and communication of neuronal networks still remain unidentified. However, the present available techniques for single-cell measurements are slow and do not allow for a high-throughput approach. We present here a CMOS compatible microelectrode array with 84 electrodes (with diameters ranging from 1.2 to 4.2 μm) that are smaller than the size of cell, thereby supporting single-cell addressability. We show controllable electroporation of a single cell by an underlying electrode while monitoring changes in the intracellular membrane potential. Further, by applying a localized electrical field between two electrodes close to a neuron while recording changes in the intracellular calcium concentration, we demonstrate activation of a single cell (∼270%, DF/F(0)), followed by a network response of the neighboring cells. The technology can be easily scaled up to larger electrode arrays (theoretically up to 137,000 electrodes/mm(2)) with active CMOS electronics integration able to perform high-throughput measurements on single cells. Copyright © 2010 Elsevier B.V. All rights reserved.

  3. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    PubMed Central

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  4. LEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering.

    PubMed

    Specht, Alicia T; Li, Jun

    2017-03-01

    To construct gene co-expression networks based on single-cell RNA-Sequencing data, we present an algorithm called LEAP, which utilizes the estimated pseudotime of the cells to find gene co-expression that involves time delay. R package LEAP available on CRAN. jun.li@nd.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  5. Single Cell Mass Cytometry for Analysis of Immune System Functional States

    PubMed Central

    Bjornson, Zach B.; Nolan, Garry P.; Fantl, Wendy J.

    2013-01-01

    Single cell mass cytometry facilitates high-dimensional, quantitative analysis of the effects of bioactive molecules on cell populations at single-cell resolution. Datasets are generated with antibody panels (upwards of 40) in which each antibody is conjugated to a polymer chelated with a stable metal isotope, usually in the Lanthanide series of the periodic table. Isotope labelled antibodies recognize surface markers to delineate cell types and intracellular signaling molecules to provide a measure of the network state—and thereby demarcating multiple cell state functions such as apoptosis, DNA damage and cell cycle. By measuring all these parameters simultaneously, the signaling state of an individual cell can be measured at its network state. This review will cover the basics of mass cytometry as well as outline steps already taken to allow it to stand aside traditional fluorescence based cytometry in the immunologist’s analytical arsenal in their study of immune states during infection. PMID:23999316

  6. A virus or more in (nearly) every cell: ubiquitous networks of virus-host interactions in extreme environments.

    PubMed

    Munson-McGee, Jacob H; Peng, Shengyun; Dewerff, Samantha; Stepanauskas, Ramunas; Whitaker, Rachel J; Weitz, Joshua S; Young, Mark J

    2018-06-01

    The application of viral and cellular metagenomics to natural environments has expanded our understanding of the structure, functioning, and diversity of microbial and viral communities. The high diversity of many communities, e.g., soils, surface ocean waters, and animal-associated microbiomes, make it difficult to establish virus-host associations at the single cell (rather than population) level, assign cellular hosts, or determine the extent of viral host range from metagenomics studies alone. Here, we combine single-cell sequencing with environmental metagenomics to characterize the structure of virus-host associations in a Yellowstone National Park (YNP) hot spring microbial community. Leveraging the relatively low diversity of the YNP environment, we are able to overlay evidence at the single-cell level with contextualized viral and cellular community structure. Combining evidence from hexanucelotide analysis, single cell read mapping, network-based analytics, and CRISPR-based inference, we conservatively estimate that >60% of cells contain at least one virus type and a majority of these cells contain two or more virus types. Of the detected virus types, nearly 50% were found in more than 2 cellular clades, indicative of a broad host range. The new lens provided by the combination of metaviromics and single-cell genomics reveals a network of virus-host interactions in extreme environments, provides evidence that extensive virus-host associations are common, and further expands the unseen impact of viruses on cellular life.

  7. Single-cell recording and stimulation with a 16k micro-nail electrode array integrated on a 0.18 μm CMOS chip.

    PubMed

    Huys, Roeland; Braeken, Dries; Jans, Danny; Stassen, Andim; Collaert, Nadine; Wouters, Jan; Loo, Josine; Severi, Simone; Vleugels, Frank; Callewaert, Geert; Verstreken, Kris; Bartic, Carmen; Eberle, Wolfgang

    2012-04-07

    To cope with the growing needs in research towards the understanding of cellular function and network dynamics, advanced micro-electrode arrays (MEAs) based on integrated complementary metal oxide semiconductor (CMOS) circuits have been increasingly reported. Although such arrays contain a large number of sensors for recording and/or stimulation, the size of the electrodes on these chips are often larger than a typical mammalian cell. Therefore, true single-cell recording and stimulation remains challenging. Single-cell resolution can be obtained by decreasing the size of the electrodes, which inherently increases the characteristic impedance and noise. Here, we present an array of 16,384 active sensors monolithically integrated on chip, realized in 0.18 μm CMOS technology for recording and stimulation of individual cells. Successful recording of electrical activity of cardiac cells with the chip, validated with intracellular whole-cell patch clamp recordings are presented, illustrating single-cell readout capability. Further, by applying a single-electrode stimulation protocol, we could pace individual cardiac cells, demonstrating single-cell addressability. This novel electrode array could help pave the way towards solving complex interactions of mammalian cellular networks. This journal is © The Royal Society of Chemistry 2012

  8. Single-cell resolution of intracellular T cell Ca2+ dynamics in response to frequency-based H2O2 stimulation.

    PubMed

    Kniss-James, Ariel S; Rivet, Catherine A; Chingozha, Loice; Lu, Hang; Kemp, Melissa L

    2017-03-01

    Adaptive immune cells, such as T cells, integrate information from their extracellular environment through complex signaling networks with exquisite sensitivity in order to direct decisions on proliferation, apoptosis, and cytokine production. These signaling networks are reliant on the interplay between finely tuned secondary messengers, such as Ca 2+ and H 2 O 2 . Frequency response analysis, originally developed in control engineering, is a tool used for discerning complex networks. This analytical technique has been shown to be useful for understanding biological systems and facilitates identification of the dominant behaviour of the system. We probed intracellular Ca 2+ dynamics in the frequency domain to investigate the complex relationship between two second messenger signaling molecules, H 2 O 2 and Ca 2+ , during T cell activation with single cell resolution. Single-cell analysis provides a unique platform for interrogating and monitoring cellular processes of interest. We utilized a previously developed microfluidic device to monitor individual T cells through time while applying a dynamic input to reveal a natural frequency of the system at approximately 2.78 mHz stimulation. Although our network was much larger with more unknown connections than previous applications, we are able to derive features from our data, observe forced oscillations associated with specific amplitudes and frequencies of stimuli, and arrive at conclusions about potential transfer function fits as well as the underlying population dynamics.

  9. Label free measurement of retinal blood cell flux, velocity, hematocrit and capillary width in the living mouse eye

    PubMed Central

    Guevara-Torres, A.; Joseph, A.; Schallek, J. B.

    2016-01-01

    Measuring blood cell dynamics within the capillaries of the living eye provides crucial information regarding the health of the microvascular network. To date, the study of single blood cell movement in this network has been obscured by optical aberrations, hindered by weak optical contrast, and often required injection of exogenous fluorescent dyes to perform measurements. Here we present a new strategy to non-invasively image single blood cells in the living mouse eye without contrast agents. Eye aberrations were corrected with an adaptive optics camera coupled with a fast, 15 kHz scanned beam orthogonal to a capillary of interest. Blood cells were imaged as they flowed past a near infrared imaging beam to which the eye is relatively insensitive. Optical contrast of cells was optimized using differential scatter of blood cells in the split-detector imaging configuration. Combined, these strategies provide label-free, non-invasive imaging of blood cells in the retina as they travel in single file in capillaries, enabling determination of cell flux, morphology, class, velocity, and rheology at the single cell level. PMID:27867728

  10. Label free measurement of retinal blood cell flux, velocity, hematocrit and capillary width in the living mouse eye.

    PubMed

    Guevara-Torres, A; Joseph, A; Schallek, J B

    2016-10-01

    Measuring blood cell dynamics within the capillaries of the living eye provides crucial information regarding the health of the microvascular network. To date, the study of single blood cell movement in this network has been obscured by optical aberrations, hindered by weak optical contrast, and often required injection of exogenous fluorescent dyes to perform measurements. Here we present a new strategy to non-invasively image single blood cells in the living mouse eye without contrast agents. Eye aberrations were corrected with an adaptive optics camera coupled with a fast, 15 kHz scanned beam orthogonal to a capillary of interest. Blood cells were imaged as they flowed past a near infrared imaging beam to which the eye is relatively insensitive. Optical contrast of cells was optimized using differential scatter of blood cells in the split-detector imaging configuration. Combined, these strategies provide label-free, non-invasive imaging of blood cells in the retina as they travel in single file in capillaries, enabling determination of cell flux, morphology, class, velocity, and rheology at the single cell level.

  11. Cell Migration in 1D and 2D Nanofiber Microenvironments.

    PubMed

    Estabridis, Horacio M; Jana, Aniket; Nain, Amrinder; Odde, David J

    2018-03-01

    Understanding how cells migrate in fibrous environments is important in wound healing, immune function, and cancer progression. A key question is how fiber orientation and network geometry influence cell movement. Here we describe a quantitative, modeling-based approach toward identifying the mechanisms by which cells migrate in fibrous geometries having well controlled orientation. Specifically, U251 glioblastoma cells were seeded onto non-electrospinning Spinneret based tunable engineering parameters fiber substrates that consist of networks of suspended 400 nm diameter nanofibers. Cells were classified based on the local fiber geometry and cell migration dynamics observed by light microscopy. Cells were found in three distinct geometries: adhering two a single fiber, adhering to two parallel fibers, and adhering to a network of orthogonal fibers. Cells adhering to a single fiber or two parallel fibers can only move in one dimension along the fiber axis, whereas cells on a network of orthogonal fibers can move in two dimensions. We found that cells move faster and more persistently in 1D geometries than in 2D, with cell migration being faster on parallel fibers than on single fibers. To explain these behaviors mechanistically, we simulated cell migration in the three different geometries using a motor-clutch based model for cell traction forces. Using nearly identical parameter sets for each of the three cases, we found that the simulated cells naturally replicated the reduced migration in 2D relative to 1D geometries. In addition, the modestly faster 1D migration on parallel fibers relative to single fibers was captured using a correspondingly modest increase in the number of clutches to reflect increased surface area of adhesion on parallel fibers. Overall, the integrated modeling and experimental analysis shows that cell migration in response to varying fibrous geometries can be explained by a simple mechanical readout of geometry via a motor-clutch mechanism.

  12. Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells

    PubMed Central

    Danaher, Patrick; Finak, Greg; Krouse, Michael; Wang, Alice; Webster, Philippa; Beechem, Joseph; Gottardo, Raphael

    2014-01-01

    Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome. PMID:25032992

  13. A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

    PubMed Central

    Sung, Myong-Hee

    2013-01-01

    Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

  14. [Prediction of the molecular response to pertubations from single cell measurements].

    PubMed

    Remacle, Françoise; Levine, Raphael D

    2014-12-01

    The response of protein signalization networks to perturbations is analysed from single cell measurements. This experimental approach allows characterizing the fluctuations in protein expression levels from cell to cell. The analysis is based on an information theoretic approach grounded in thermodynamics leading to a quantitative version of Le Chatelier principle which allows to predict the molecular response. Two systems are investigated: human macrophages subjected to lipopolysaccharide challenge, analogous to the immune response against Gram-negative bacteria and the response of the proteins involved in the mTOR signalizing network of GBM cancer cells to changes in partial oxygen pressure. © 2014 médecine/sciences – Inserm.

  15. Functional magnetic resonance microscopy at single-cell resolution in Aplysia californica

    PubMed Central

    Radecki, Guillaume; Nargeot, Romuald; Jelescu, Ileana Ozana; Le Bihan, Denis; Ciobanu, Luisa

    2014-01-01

    In this work, we show the feasibility of performing functional MRI studies with single-cell resolution. At ultrahigh magnetic field, manganese-enhanced magnetic resonance microscopy allows the identification of most motor neurons in the buccal network of Aplysia at low, nontoxic Mn2+ concentrations. We establish that Mn2+ accumulates intracellularly on injection into the living Aplysia and that its concentration increases when the animals are presented with a sensory stimulus. We also show that we can distinguish between neuronal activities elicited by different types of stimuli. This method opens up a new avenue into probing the functional organization and plasticity of neuronal networks involved in goal-directed behaviors with single-cell resolution. PMID:24872449

  16. Tracing the temporal-spatial transcriptome landscapes of the human fetal digestive tract using single-cell RNA-sequencing.

    PubMed

    Gao, Shuai; Yan, Liying; Wang, Rui; Li, Jingyun; Yong, Jun; Zhou, Xin; Wei, Yuan; Wu, Xinglong; Wang, Xiaoye; Fan, Xiaoying; Yan, Jie; Zhi, Xu; Gao, Yun; Guo, Hongshan; Jin, Xiao; Wang, Wendong; Mao, Yunuo; Wang, Fengchao; Wen, Lu; Fu, Wei; Ge, Hao; Qiao, Jie; Tang, Fuchou

    2018-06-01

    The development of the digestive tract is critical for proper food digestion and nutrient absorption. Here, we analyse the main organs of the digestive tract, including the oesophagus, stomach, small intestine and large intestine, from human embryos between 6 and 25 weeks of gestation as well as the large intestine from adults using single-cell RNA-seq analyses. In total, 5,227 individual cells are analysed and 40 cell types clearly identified. Their crucial biological features, including developmental processes, signalling pathways, cell cycle, nutrient digestion and absorption metabolism, and transcription factor networks, are systematically revealed. Moreover, the differentiation and maturation processes of the large intestine are thoroughly investigated by comparing the corresponding transcriptome profiles between embryonic and adult stages. Our work offers a rich resource for investigating the gene regulation networks of the human fetal digestive tract and adult large intestine at single-cell resolution.

  17. Light-patterning of synthetic tissues with single droplet resolution.

    PubMed

    Booth, Michael J; Restrepo Schild, Vanessa; Box, Stuart J; Bayley, Hagan

    2017-08-24

    Synthetic tissues can be generated by forming networks of aqueous droplets in lipid-containing oil. Each droplet contains a cell-free expression system and is connected to its neighbor through a lipid bilayer. In the present work, we have demonstrated precise external control of such networks by activating protein expression within single droplets, by using light-activated DNA to encode either a fluorescent or a pore-forming protein. By controlling the extent of activation, synthetic tissues were generated with graded levels of protein expression in patterns of single droplets. Further, we have demonstrated reversible activation within individual compartments in synthetic tissues by turning a fluorescent protein on-and-off. This is the first example of the high-resolution patterning of droplet networks, following their formation. Single-droplet control will be essential to power subsets of compartments within synthetic tissues or to stimulate subsets of cells when synthetic tissues are interfaced with living tissues.

  18. Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

    PubMed Central

    Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

    2017-01-01

    Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

  19. Construction of Injectable Double-Network Hydrogels for Cell Delivery.

    PubMed

    Yan, Yan; Li, Mengnan; Yang, Di; Wang, Qian; Liang, Fuxin; Qu, Xiaozhong; Qiu, Dong; Yang, Zhenzhong

    2017-07-10

    Herein we present a unique method of using dynamic cross-links, which are dynamic covalent bonding and ionic interaction, for the construction of injectable double-network (DN) hydrogels, with the objective of cell delivery for cartilage repair. Glycol chitosan and dibenzaldhyde capped poly(ethylene oxide) formed the first network, while calcium alginate formed the second one, and in the resultant DN hydrogel, either of the networks could be selectively removed. The moduli of the DN hydrogel were significantly improved compared to that of the parent single-network hydrogels and were tunable by changing the chemical components. In situ 3D cell encapsulation could be easily performed by mixing cell suspension to the polymer solutions and transferred through a syringe needle before sol-gel transition. Cell proliferation and mediated differentiation of mouse chondrogenic cells were achieved in the DN hydrogel extracellular matrix.

  20. Network Characteristics of Collective Chemosensing

    NASA Astrophysics Data System (ADS)

    Sun, Bo; Duclos, Guillaume; Stone, Howard A.

    2013-04-01

    The collective chemosensing of nonexcitable mammalian cells involves a biochemical network that features gap junction communications and heterogeneous single cell activities. To understand the integrated multicellular chemosensing, we study the calcium dynamics of micropatterned fibroblast cell colonies in response to adenosine triphosphate (ATP) stimulation. We find that the cross-correlation function between the responses of individual cells decays with topological distance as a power law for large colonies and much faster for smaller colonies. Furthermore, the strongly correlated cell pairs tend to form clusters and are more likely to exceed the percolation threshold. At a given topological distance, the cross-correlations exhibit characteristics of Poisson distributions, which allows us to estimate the unitary conductance of a single gap junction which is in good agreement with direct experimental measurements.

  1. Single cell transcriptomics to explore the immune system in health and disease†

    PubMed Central

    Regev, Aviv; Teichmann, Sarah A.

    2017-01-01

    The immune system varies in cell types, states, and locations. The complex networks, interactions and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as, massively-parallel single cell RNA-Seq and sophisticated computational methods are catalysing a revolution in our understanding of immunology. Here, we provide an overview of the state of single cell genomics methods and an outlook on the use of single-cell techniques to decipher the adaptive and innate components of immunity. PMID:28983043

  2. Accurate analytic solution of chemical master equations for gene regulation networks in a single cell

    NASA Astrophysics Data System (ADS)

    Huang, Guan-Rong; Saakian, David B.; Hu, Chin-Kun

    2018-01-01

    Studying gene regulation networks in a single cell is an important, interesting, and hot research topic of molecular biology. Such process can be described by chemical master equations (CMEs). We propose a Hamilton-Jacobi equation method with finite-size corrections to solve such CMEs accurately at the intermediate region of switching, where switching rate is comparable to fast protein production rate. We applied this approach to a model of self-regulating proteins [H. Ge et al., Phys. Rev. Lett. 114, 078101 (2015), 10.1103/PhysRevLett.114.078101] and found that as a parameter related to inducer concentration increases the probability of protein production changes from unimodal to bimodal, then to unimodal, consistent with phenotype switching observed in a single cell.

  3. Extracting microtubule networks from superresolution single-molecule localization microscopy data

    PubMed Central

    Zhang, Zhen; Nishimura, Yukako; Kanchanawong, Pakorn

    2017-01-01

    Microtubule filaments form ubiquitous networks that specify spatial organization in cells. However, quantitative analysis of microtubule networks is hampered by their complex architecture, limiting insights into the interplay between their organization and cellular functions. Although superresolution microscopy has greatly facilitated high-resolution imaging of microtubule filaments, extraction of complete filament networks from such data sets is challenging. Here we describe a computational tool for automated retrieval of microtubule filaments from single-molecule-localization–based superresolution microscopy images. We present a user-friendly, graphically interfaced implementation and a quantitative analysis of microtubule network architecture phenotypes in fibroblasts. PMID:27852898

  4. Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons.

    PubMed

    Bernardi, Davide; Lindner, Benjamin

    2017-06-30

    Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.

  5. Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons

    NASA Astrophysics Data System (ADS)

    Bernardi, Davide; Lindner, Benjamin

    2017-06-01

    Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.

  6. Model-based design of RNA hybridization networks implemented in living cells

    PubMed Central

    Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter

    2017-01-01

    Abstract Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. PMID:28934501

  7. Analysis of neuronal cells of dissociated primary culture on high-density CMOS electrode array

    PubMed Central

    Matsuda, Eiko; Mita, Takeshi; Hubert, Julien; Bakkum, Douglas; Frey, Urs; Hierlemann, Andreas; Takahashi, Hirokazu; Ikegami, Takashi

    2017-01-01

    Spontaneous development of neuronal cells was recorded around 4–34 days in vitro (DIV) with high-density CMOS array, which enables detailed study of the spatio-temporal activity of neuronal culture. We used the CMOS array to characterize the evolution of the inter-spike interval (ISI) distribution from putative single neurons, and estimate the network structure based on transfer entropy analysis, where each node corresponds to a single neuron. We observed that the ISI distributions gradually obeyed the power law with maturation of the network. The amount of information transferred between neurons increased at the early stage of development, but decreased as the network matured. These results suggest that both ISI and transfer entropy were very useful for characterizing the dynamic development of cultured neural cells over a few weeks. PMID:24109870

  8. Dynamics of Bacterial Gene Regulatory Networks.

    PubMed

    Shis, David L; Bennett, Matthew R; Igoshin, Oleg A

    2018-05-20

    The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

  9. Calculation of 3D genome structures for comparison of chromosome conformation capture experiments with microscopy: An evaluation of single-cell Hi-C protocols.

    PubMed

    Lando, David; Stevens, Tim J; Basu, Srinjan; Laue, Ernest D

    2018-01-01

    Single-cell chromosome conformation capture approaches are revealing the extent of cell-to-cell variability in the organization and packaging of genomes. These single-cell methods, unlike their multi-cell counterparts, allow straightforward computation of realistic chromosome conformations that may be compared and combined with other, independent, techniques to study 3D structure. Here we discuss how single-cell Hi-C and subsequent 3D genome structure determination allows comparison with data from microscopy. We then carry out a systematic evaluation of recently published single-cell Hi-C datasets to establish a computational approach for the evaluation of single-cell Hi-C protocols. We show that the calculation of genome structures provides a useful tool for assessing the quality of single-cell Hi-C data because it requires a self-consistent network of interactions, relating to the underlying 3D conformation, with few errors, as well as sufficient longer-range cis- and trans-chromosomal contacts.

  10. Limiting Energy Dissipation Induces Glassy Kinetics in Single-Cell High-Precision Responses

    PubMed Central

    Das, Jayajit

    2016-01-01

    Single cells often generate precise responses by involving dissipative out-of-thermodynamic-equilibrium processes in signaling networks. The available free energy to fuel these processes could become limited depending on the metabolic state of an individual cell. How does limiting dissipation affect the kinetics of high-precision responses in single cells? I address this question in the context of a kinetic proofreading scheme used in a simple model of early-time T cell signaling. Using exact analytical calculations and numerical simulations, I show that limiting dissipation qualitatively changes the kinetics in single cells marked by emergence of slow kinetics, large cell-to-cell variations of copy numbers, temporally correlated stochastic events (dynamic facilitation), and ergodicity breaking. Thus, constraints in energy dissipation, in addition to negatively affecting ligand discrimination in T cells, can create a fundamental difficulty in determining single-cell kinetics from cell-population results. PMID:26958894

  11. Structure, function, and self-assembly of single network gyroid (I4132) photonic crystals in butterfly wing scales.

    PubMed

    Saranathan, Vinodkumar; Osuji, Chinedum O; Mochrie, Simon G J; Noh, Heeso; Narayanan, Suresh; Sandy, Alec; Dufresne, Eric R; Prum, Richard O

    2010-06-29

    Complex three-dimensional biophotonic nanostructures produce the vivid structural colors of many butterfly wing scales, but their exact nanoscale organization is uncertain. We used small angle X-ray scattering (SAXS) on single scales to characterize the 3D photonic nanostructures of five butterfly species from two families (Papilionidae, Lycaenidae). We identify these chitin and air nanostructures as single network gyroid (I4(1)32) photonic crystals. We describe their optical function from SAXS data and photonic band-gap modeling. Butterflies apparently grow these gyroid nanostructures by exploiting the self-organizing physical dynamics of biological lipid-bilayer membranes. These butterfly photonic nanostructures initially develop within scale cells as a core-shell double gyroid (Ia3d), as seen in block-copolymer systems, with a pentacontinuous volume comprised of extracellular space, cell plasma membrane, cellular cytoplasm, smooth endoplasmic reticulum (SER) membrane, and intra-SER lumen. This double gyroid nanostructure is subsequently transformed into a single gyroid network through the deposition of chitin in the extracellular space and the degeneration of the rest of the cell. The butterflies develop the thermodynamically favored double gyroid precursors as a route to the optically more efficient single gyroid nanostructures. Current approaches to photonic crystal engineering also aim to produce single gyroid motifs. The biologically derived photonic nanostructures characterized here may offer a convenient template for producing optical devices based on biomimicry or direct dielectric infiltration.

  12. Structure, function, and self-assembly of single network gyroid (I4132) photonic crystals in butterfly wing scales

    PubMed Central

    Saranathan, Vinodkumar; Osuji, Chinedum O.; Mochrie, Simon G. J.; Noh, Heeso; Narayanan, Suresh; Sandy, Alec; Dufresne, Eric R.; Prum, Richard O.

    2010-01-01

    Complex three-dimensional biophotonic nanostructures produce the vivid structural colors of many butterfly wing scales, but their exact nanoscale organization is uncertain. We used small angle X-ray scattering (SAXS) on single scales to characterize the 3D photonic nanostructures of five butterfly species from two families (Papilionidae, Lycaenidae). We identify these chitin and air nanostructures as single network gyroid (I4132) photonic crystals. We describe their optical function from SAXS data and photonic band-gap modeling. Butterflies apparently grow these gyroid nanostructures by exploiting the self-organizing physical dynamics of biological lipid-bilayer membranes. These butterfly photonic nanostructures initially develop within scale cells as a core-shell double gyroid (Ia3d), as seen in block-copolymer systems, with a pentacontinuous volume comprised of extracellular space, cell plasma membrane, cellular cytoplasm, smooth endoplasmic reticulum (SER) membrane, and intra-SER lumen. This double gyroid nanostructure is subsequently transformed into a single gyroid network through the deposition of chitin in the extracellular space and the degeneration of the rest of the cell. The butterflies develop the thermodynamically favored double gyroid precursors as a route to the optically more efficient single gyroid nanostructures. Current approaches to photonic crystal engineering also aim to produce single gyroid motifs. The biologically derived photonic nanostructures characterized here may offer a convenient template for producing optical devices based on biomimicry or direct dielectric infiltration. PMID:20547870

  13. Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

    NASA Astrophysics Data System (ADS)

    Teschendorff, Andrew E.; Enver, Tariq

    2017-06-01

    The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.

  14. Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

    PubMed Central

    Teschendorff, Andrew E.; Enver, Tariq

    2017-01-01

    The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836

  15. Single cell systems biology by super-resolution imaging and combinatorial labeling

    PubMed Central

    Lubeck, Eric; Cai, Long

    2012-01-01

    Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral separability of fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using Fluorescence in situ Hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured the mRNA levels of 32 genes simultaneously in single S. cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells provides a natural approach to bring systems biology into single cells. PMID:22660740

  16. Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP.

    PubMed

    Twig, Gilad; Graf, Solomon A; Wikstrom, Jakob D; Mohamed, Hibo; Haigh, Sarah E; Elorza, Alvaro; Deutsch, Motti; Zurgil, Naomi; Reynolds, Nicole; Shirihai, Orian S

    2006-07-01

    Assembly of mitochondria into networks supports fuel metabolism and calcium transport and is involved in the cellular response to apoptotic stimuli. A mitochondrial network is defined as a continuous matrix lumen whose boundaries limit molecular diffusion. Observation of individual networks has proven challenging in live cells that possess dense populations of mitochondria. Investigation into the electrical and morphological properties of mitochondrial networks has therefore not yielded consistent conclusions. In this study we used matrix-targeted, photoactivatable green fluorescent protein to tag single mitochondrial networks. This approach, coupled with real-time monitoring of mitochondrial membrane potential, permitted the examination of matrix lumen continuity and fusion and fission events over time. We found that adjacent and intertwined mitochondrial structures often represent a collection of distinct networks. We additionally found that all areas of a single network are invariably equipotential, suggesting that a heterogeneous pattern of membrane potential within a cell's mitochondria represents differences between discrete networks. Interestingly, fission events frequently occurred without any gross morphological changes and particularly without fragmentation. These events, which are invisible under standard confocal microscopy, redefine the mitochondrial network boundaries and result in electrically disconnected daughter units.

  17. An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability

    PubMed Central

    Schütte, Judith; Wang, Huange; Antoniou, Stella; Jarratt, Andrew; Wilson, Nicola K; Riepsaame, Joey; Calero-Nieto, Fernando J; Moignard, Victoria; Basilico, Silvia; Kinston, Sarah J; Hannah, Rebecca L; Chan, Mun Chiang; Nürnberg, Sylvia T; Ouwehand, Willem H; Bonzanni, Nicola; de Bruijn, Marella FTR; Göttgens, Berthold

    2016-01-01

    Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes. DOI: http://dx.doi.org/10.7554/eLife.11469.001 PMID:26901438

  18. Lineage-specific enhancers activate self-renewal genes in macrophages and embryonic stem cells

    PubMed Central

    Soucie, Erinn L.; Weng, Ziming; Geirsdóttir, Laufey; Molawi, Kaaweh; Maurizio, Julien; Fenouil, Romain; Mossadegh-Keller, Noushine; Gimenez, Gregory; VanHille, Laurent; Beniazza, Meryam; Favret, Jeremy; Berruyer, Carole; Perrin, Pierre; Hacohen, Nir; Andrau, J.-C.; Ferrier, Pierre; Dubreuil, Patrice; Sidow, Arend; Sieweke, Michael H.

    2016-01-01

    Differentiated macrophages can self-renew in tissues and expand long-term in culture, but the gene regulatory mechanisms that accomplish self-renewal in the differentiated state have remained unknown. Here we show that in mice, the transcription factors MafB and c-Maf repress a macrophage-specific enhancer repertoire associated with a gene network controlling self-renewal. Single cell analysis revealed that, in vivo, proliferating resident macrophages can access this network by transient down-regulation of Maf transcription factors. The network also controls embryonic stem cell self-renewal but is associated with distinct embryonic stem cell-specific enhancers. This indicates that distinct lineage-specific enhancer platforms regulate a shared network of genes that control self-renewal potential in both stem and mature cells. PMID:26797145

  19. Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process

    PubMed Central

    Boullu, Loïs; Morin, Valérie; Vallin, Elodie; Guillemin, Anissa; Papili Gao, Nan; Cosette, Jérémie; Arnaud, Ophélie; Kupiec, Jean-Jacques; Espinasse, Thibault

    2016-01-01

    In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network. PMID:28027290

  20. Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process.

    PubMed

    Richard, Angélique; Boullu, Loïs; Herbach, Ulysse; Bonnafoux, Arnaud; Morin, Valérie; Vallin, Elodie; Guillemin, Anissa; Papili Gao, Nan; Gunawan, Rudiyanto; Cosette, Jérémie; Arnaud, Ophélie; Kupiec, Jean-Jacques; Espinasse, Thibault; Gonin-Giraud, Sandrine; Gandrillon, Olivier

    2016-12-01

    In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a "simple" program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.

  1. Inhibition of the interactions between eosinophil cationic protein and airway epithelial cells by traditional Chinese herbs.

    PubMed

    Chang, Hao-Teng; Tseng, Louis J; Hung, Ta-Jen; Kao, Blacky T; Lin, Wei-Yong; Fan, Tan-chi; Chang, Margaret Dah-Tsyr; Pai, Tun-Wen

    2010-09-13

    The eosinophil cationic protein (ECP) is cytotoxic to bacteria, viruses, parasites and mammalian cells. Cells are damaged via processes of pore formation, permeability alteration and membrane leaking. Some clinical studies indicate that ECP gathers in the bronchial tract of asthma sufferers, damages bronchial and airway epithelial cells, and leads to in breathing tract inflammation; therefore, prevention of the cytotoxicity caused by ECP may serve as an approach to treat airway inflammation. To achieve the purpose, reduction of the ECP-cell interactions is rational. In this work, the Chinese herbal combinative network was generated to predict and identify the functional herbs from the pools of prescriptions. It was useful to select the node herbs and to demonstrate the relative binding ability between ECP and Beas-2B cells with or withour herb treatments. Eighty three Chinese herbs and prescriptions were tested and five effective herbs and six prescription candidates were selected. On the basis of effective single-herbal drugs and prescriptions, a combinative network was generated. We found that a single herb, Gan-cao, served as a node connecting five prescriptions. In addition, Sheng-di-huang, Dang-guei and Mu-tong also appeared in five, four and three kinds of prescriptions, respectively. The extracts of these three herbs indeed effectively inhibited the interactions between ECP and Beas-2B cells. According to the Chinese herbal combinative network, eight of the effective herbal extracts showed inhibitory effects for ECP internalizing into Beas-2B cells. The major components of Gang-cao and Sheng-di-huang, glycyrrhizic acid and verbascose, respectively, reduced the binding affinity between ECP and cells effectively. Since these Chinese herbs reduced the binding affinity between ECP and cells and inhibited subsequent ECP entrance into cells, they were potential for mitigating the airway inflammation symptoms. Additionally, we mentioned a new concept to study the Chinese herbs using combinative network in the field of systems biology. The functional single herbs could be identified from the set of prescriptions.

  2. Single-Cell mRNA-Seq Using the Fluidigm C1 System and Integrated Fluidics Circuits.

    PubMed

    Gong, Haibiao; Do, Devin; Ramakrishnan, Ramesh

    2018-01-01

    Single-cell mRNA-seq is a valuable tool to dissect expression profiles and to understand the regulatory network of genes. Microfluidics is well suited for single-cell analysis owing both to the small volume of the reaction chambers and easiness of automation. Here we describe the workflow of single-cell mRNA-seq using C1 IFC, which can isolate and process up to 96 cells. Both on-chip procedure (lysis, reverse transcription, and preamplification PCR) and off-chip sequencing library preparation protocols are described. The workflow generates full-length mRNA information, which is more valuable compared to 3' end counting method for many applications.

  3. Network embedding-based representation learning for single cell RNA-seq data.

    PubMed

    Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

    2017-11-02

    Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. An Empirically Calibrated Model of Cell Fate Decision Following Viral Infection

    NASA Astrophysics Data System (ADS)

    Coleman, Seth; Igoshin, Oleg; Golding, Ido

    The life cycle of the virus (phage) lambda is an established paradigm for the way genetic networks drive cell fate decisions. But despite decades of interrogation, we are still unable to theoretically predict whether the infection of a given cell will result in cell death or viral dormancy. The poor predictive power of current models reflects the absence of quantitative experimental data describing the regulatory interactions between different lambda genes. To address this gap, we are constructing a theoretical model that captures the known interactions in the lambda network. Model assumptions and parameters are calibrated using new single-cell data from our lab, describing the activity of lambda genes at single-molecule resolution. We began with a mean-field model, aimed at exploring the population averaged gene-expression trajectories under different initial conditions. Next, we will develop a stochastic formulation, to capture the differences between individual cells within the population. The eventual goal is to identify how the post-infection decision is driven by the interplay between network topology, initial conditions, and stochastic effects. The insights gained here will inform our understanding of cell fate choices in more complex cellular systems.

  5. Model-based design of RNA hybridization networks implemented in living cells.

    PubMed

    Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter; Daròs, José-Antonio; Jaramillo, Alfonso

    2017-09-19

    Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Disrupting the Networks of Cancer

    PubMed Central

    Camacho, Daniel F.; Pienta, Kenneth J.

    2014-01-01

    Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. PMID:22442061

  7. Disrupting the networks of cancer.

    PubMed

    Camacho, Daniel F; Pienta, Kenneth J

    2012-05-15

    Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. ©2012 AACR.

  8. Tensegrity II. How structural networks influence cellular information processing networks

    NASA Technical Reports Server (NTRS)

    Ingber, Donald E.

    2003-01-01

    The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

  9. Programming Morphogenesis through Systems and Synthetic Biology.

    PubMed

    Velazquez, Jeremy J; Su, Emily; Cahan, Patrick; Ebrahimkhani, Mo R

    2018-04-01

    Mammalian tissue development is an intricate, spatiotemporal process of self-organization that emerges from gene regulatory networks of differentiating stem cells. A major goal in stem cell biology is to gain a sufficient understanding of gene regulatory networks and cell-cell interactions to enable the reliable and robust engineering of morphogenesis. Here, we review advances in synthetic biology, single cell genomics, and multiscale modeling, which, when synthesized, provide a framework to achieve the ambitious goal of programming morphogenesis in complex tissues and organoids. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Lineage-specific enhancers activate self-renewal genes in macrophages and embryonic stem cells.

    PubMed

    Soucie, Erinn L; Weng, Ziming; Geirsdóttir, Laufey; Molawi, Kaaweh; Maurizio, Julien; Fenouil, Romain; Mossadegh-Keller, Noushine; Gimenez, Gregory; VanHille, Laurent; Beniazza, Meryam; Favret, Jeremy; Berruyer, Carole; Perrin, Pierre; Hacohen, Nir; Andrau, J-C; Ferrier, Pierre; Dubreuil, Patrice; Sidow, Arend; Sieweke, Michael H

    2016-02-12

    Differentiated macrophages can self-renew in tissues and expand long term in culture, but the gene regulatory mechanisms that accomplish self-renewal in the differentiated state have remained unknown. Here we show that in mice, the transcription factors MafB and c-Maf repress a macrophage-specific enhancer repertoire associated with a gene network that controls self-renewal. Single-cell analysis revealed that, in vivo, proliferating resident macrophages can access this network by transient down-regulation of Maf transcription factors. The network also controls embryonic stem cell self-renewal but is associated with distinct embryonic stem cell-specific enhancers. This indicates that distinct lineage-specific enhancer platforms regulate a shared network of genes that control self-renewal potential in both stem and mature cells. Copyright © 2016, American Association for the Advancement of Science.

  11. Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks

    PubMed Central

    Samusik, Nikolay; Wang, Xiaowei; Guan, Leying; Nolan, Garry P.

    2017-01-01

    Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be quickly and dramatically amplified with increasing number of samples. To overcome this limitation, we developed Partition-Assisted Clustering and Multiple Alignments of Networks (PAC-MAN) for the fast automatic identification of cell populations in CyTOF data closely matching that of expert manual-discovery, and for alignments between subpopulations across samples to define dataset-level cellular states. PAC-MAN is computationally efficient, allowing the management of very large CyTOF datasets, which are increasingly common in clinical studies and cancer studies that monitor various tissue samples for each subject. PMID:29281633

  12. Creation of defined single cell resolution neuronal circuits on microelectrode arrays

    NASA Astrophysics Data System (ADS)

    Pirlo, Russell Kirk

    2009-12-01

    The way cell-cell organization of neuronal networks influences activity and facilitates function is not well understood. Microelectrode arrays (MEAs) and advancing cell patterning technologies have enabled access to and control of in vitro neuronal networks spawning much new research in neuroscience and neuroengineering. We propose that small, simple networks of neurons with defined circuitry may serve as valuable research models where every connection can be analyzed, controlled and manipulated. Towards the goal of creating such neuronal networks we have applied microfabricated elastomeric membranes, surface modification and our unique laser cell patterning system to create defined neuronal circuits with single-cell precision on MEAs. Definition of synaptic connectivity was imposed by the 3D physical constraints of polydimethylsiloxane elastomeric membranes. The membranes had 20mum clear-through holes and 2-3mum deep channels which when applied to the surface of the MEA formed microwells to confine neurons to electrodes connected via shallow tunnels to direct neurite outgrowth. Tapering and turning of channels was used to influence neurite polarity. Biocompatibility of the membranes was increased by vacuum baking, oligomer extraction, and autoclaving. Membranes were bound to the MEA by oxygen plasma treatment and heated pressure. The MEA/membrane surface was treated with oxygen plasma, poly-D-lysine and laminin to improve neuron attachment, survival and neurite outgrowth. Prior to cell patterning the outer edge of culture area was seeded with 5x10 5 cells per cm and incubated for 2 days. Single embryonic day 7 chick forebrain neurons were then patterned into the microwells and onto the electrodes using our laser cell patterning system. Patterned neurons successfully attached to and were confined to the electrodes. Neurites extended through the interconnecting channels and connected with adjacent neurons. These results demonstrate that neuronal circuits can be created with clearly defined circuitry and a one-to-one neuron-electrode ratio. The techniques and processes described here may be used in future research to create defined neuronal circuits to model in vivo circuits and study neuronal network processing.

  13. Motion in partially and fully cross-linked F-actin networks

    NASA Astrophysics Data System (ADS)

    Morris, Eliza; Ehrlicher, Allen; Weitz, David

    2012-02-01

    Single molecule experiments have measured stall forces and procession rates of molecular motors on isolated cytoskeletal fibers in Newtonian fluids. But in the cell, these motors are transporting cargo through a highly complex cytoskeletal network. To compare these single molecule results to the forces exerted by motors within the cell, an evaluation of the response of the cytoskeletal network is needed. Using magnetic tweezers and fluorescence confocal microscopy we observe and quantify the relationship between bead motion and filament response in F-actin networks both partially and fully cross-linked with filamin We find that when the transition from full to partial cross-linking is brought about by a decrease in cross-linker concentration there is a simultaneous decline in the elasticity of the network, but the response of the bead remains qualitatively similar. However, when the cross-linking is reduced through a shortening of the F-actin filaments the bead response is completely altered. The characteristics of the altered bead response will be discussed here.

  14. Mechanically induced intercellular calcium communication in confined endothelial structures.

    PubMed

    Junkin, Michael; Lu, Yi; Long, Juexuan; Deymier, Pierre A; Hoying, James B; Wong, Pak Kin

    2013-03-01

    Calcium signaling in the diverse vascular structures is regulated by a wide range of mechanical and biochemical factors to maintain essential physiological functions of the vasculature. To properly transmit information, the intercellular calcium communication mechanism must be robust against various conditions in the cellular microenvironment. Using plasma lithography geometric confinement, we investigate mechanically induced calcium wave propagation in networks of human umbilical vein endothelial cells organized. Endothelial cell networks with confined architectures were stimulated at the single cell level, including using capacitive force probes. Calcium wave propagation in the network was observed using fluorescence calcium imaging. We show that mechanically induced calcium signaling in the endothelial networks is dynamically regulated against a wide range of probing forces and repeated stimulations. The calcium wave is able to propagate consistently in various dimensions from monolayers to individual cell chains, and in different topologies from linear patterns to cell junctions. Our results reveal that calcium signaling provides a robust mechanism for cell-cell communication in networks of endothelial cells despite the diversity of the microenvironmental inputs and complexity of vascular structures. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Limiting Energy Dissipation Induces Glassy Kinetics in Single-Cell High-Precision Responses.

    PubMed

    Das, Jayajit

    2016-03-08

    Single cells often generate precise responses by involving dissipative out-of-thermodynamic-equilibrium processes in signaling networks. The available free energy to fuel these processes could become limited depending on the metabolic state of an individual cell. How does limiting dissipation affect the kinetics of high-precision responses in single cells? I address this question in the context of a kinetic proofreading scheme used in a simple model of early-time T cell signaling. Using exact analytical calculations and numerical simulations, I show that limiting dissipation qualitatively changes the kinetics in single cells marked by emergence of slow kinetics, large cell-to-cell variations of copy numbers, temporally correlated stochastic events (dynamic facilitation), and ergodicity breaking. Thus, constraints in energy dissipation, in addition to negatively affecting ligand discrimination in T cells, can create a fundamental difficulty in determining single-cell kinetics from cell-population results. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  16. Digital Single-Cell Analysis of Plant Organ Development Using 3DCellAtlas[OPEN

    PubMed Central

    Montenegro-Johnson, Thomas D.; Stamm, Petra; Strauss, Soeren; Topham, Alexander T.; Tsagris, Michail; Wood, Andrew T.A.; Smith, Richard S.; Bassel, George W.

    2015-01-01

    Diverse molecular networks underlying plant growth and development are rapidly being uncovered. Integrating these data into the spatial and temporal context of dynamic organ growth remains a technical challenge. We developed 3DCellAtlas, an integrative computational pipeline that semiautomatically identifies cell types and quantifies both 3D cellular anisotropy and reporter abundance at single-cell resolution across whole plant organs. Cell identification is no less than 97.8% accurate and does not require transgenic lineage markers or reference atlases. Cell positions within organs are defined using an internal indexing system generating cellular level organ atlases where data from multiple samples can be integrated. Using this approach, we quantified the organ-wide cell-type-specific 3D cellular anisotropy driving Arabidopsis thaliana hypocotyl elongation. The impact ethylene has on hypocotyl 3D cell anisotropy identified the preferential growth of endodermis in response to this hormone. The spatiotemporal dynamics of the endogenous DELLA protein RGA, expansin gene EXPA3, and cell expansion was quantified within distinct cell types of Arabidopsis roots. A significant regulatory relationship between RGA, EXPA3, and growth was present in the epidermis and endodermis. The use of single-cell analyses of plant development enables the dynamics of diverse regulatory networks to be integrated with 3D organ growth. PMID:25901089

  17. A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.

    PubMed

    Hu, Yongli; Hase, Takeshi; Li, Hui Peng; Prabhakar, Shyam; Kitano, Hiroaki; Ng, See Kiong; Ghosh, Samik; Wee, Lawrence Jin Kiat

    2016-12-22

    The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a heterogeneous population of cells, one at a time. However, till date, there has not been a suitable computational methodology for the analysis of such intricate deluge of data, in particular techniques which will aid the identification of the unique transcriptomic profiles difference between the different cellular subtypes. In this paper, we describe the novel methodology for the analysis of single-cell RNA-seq data, obtained from neocortical cells and neural progenitor cells, using machine learning algorithms (Support Vector machine (SVM) and Random Forest (RF)). Thirty-eight key transcripts were identified, using the SVM-based recursive feature elimination (SVM-RFE) method of feature selection, to best differentiate developing neocortical cells from neural progenitor cells in the SVM and RF classifiers built. Also, these genes possessed a higher discriminative power (enhanced prediction accuracy) as compared commonly used statistical techniques or geneset-based approaches. Further downstream network reconstruction analysis was carried out to unravel hidden general regulatory networks where novel interactions could be further validated in web-lab experimentation and be useful candidates to be targeted for the treatment of neuronal developmental diseases. This novel approach reported for is able to identify transcripts, with reported neuronal involvement, which optimally differentiate neocortical cells and neural progenitor cells. It is believed to be extensible and applicable to other single-cell RNA-seq expression profiles like that of the study of the cancer progression and treatment within a highly heterogeneous tumour.

  18. Flow cytometry in the post fluorescence era.

    PubMed

    Nolan, Garry P

    2011-12-01

    While flow cytometry once enabled researchers to examine 10--15 cell surface parameters, new mass flow cytometry technology enables interrogation of up to 45 parameters on a single cell. This new technology has increased understanding of cell expression and how cells differentiate during hematopoiesis. Using this information, knowledge of leukemia cell biology has also increased. Other new technologies, such as SPADE analysis and single cell network profiling (SCNP), are enabling researchers to put different cancers into more biologically similar categories and have the potential to enable more personalized medicine. Copyright © 2011. Published by Elsevier Ltd.

  19. The CRYPTOCHROME photoreceptor gates PDF neuropeptide signaling to set circadian network hierarchy in Drosophila.

    PubMed

    Zhang, Luoying; Lear, Bridget C; Seluzicki, Adam; Allada, Ravi

    2009-12-15

    Circadian clocks in the brain are organized as coupled oscillators that integrate seasonal cues such as light and temperature to time daily behaviors. In Drosophila, the PIGMENT DISPERSING FACTOR (PDF) neuropeptide-expressing morning (M) and non-PDF evening (E) cells are coupled cell groups important for morning and evening behavior, respectively. Depending on day length, either M cells (short days) or E cells (long days) dictate both the morning and the evening phase, a phenomenon that we term network hierarchy. To examine the role of PDF in light-dark conditions, we examined flies lacking both the PDF receptor (PDFR) and the circadian photoreceptor CRYPTOCHROME (CRY). We found that subsets of E cells exhibit molecular oscillations antiphase to those of wild-type flies, single cry mutants, or single Pdfr mutants, demonstrating a potent role for PDF in light-mediated entrainment, specifically in the absence of CRY. Moreover, we find that the evening behavioral phase is more strongly reset by PDF(+) M cells in the absence of CRY. On the basis of our findings, we propose that CRY can gate PDF signaling to determine behavioral phase and network hierarchy.

  20. Strategies for Increasing Pancreatic Tumor Immunogenicity

    PubMed Central

    Johnson, Burles A.; Yarchoan, Mark; Lee, Valerie; Laheru, Daniel A.; Jaffee, Elizabeth M.

    2017-01-01

    Immunotherapy has changed the standard of care for multiple deadly cancers including lung, head and neck, gastric, and some colorectal cancers. However, single agent immunotherapy has had little effect in pancreatic adenocarcinoma (PDAC). Increasing evidence suggests that the PDAC microenvironment is comprised of an intricate network of signals between immune cells, PDAC cells, and stroma, resulting in an immunosuppressive environment resistant to single agent immunotherapies. In this review, we discuss differences between immunotherapy sensitive cancers and PDAC, the complex interactions between PDAC stroma and suppressive tumor infiltrating cells that facilitate PDAC development and progression, the immunologic targets within these complex networks that are drugable, and data supporting combination drug approaches that modulate multiple PDAC signals, which should lead to improved clinical outcomes. PMID:28373364

  1. From molecular noise to behavioural variability in a single bacterium

    NASA Astrophysics Data System (ADS)

    Korobkova, Ekaterina; Emonet, Thierry; Vilar, Jose M. G.; Shimizu, Thomas S.; Cluzel, Philippe

    2004-04-01

    The chemotaxis network that governs the motion of Escherichia coli has long been studied to gain a general understanding of signal transduction. Although this pathway is composed of just a few components, it exhibits some essential characteristics of biological complexity, such as adaptation and response to environmental signals. In studying intracellular networks, most experiments and mathematical models have assumed that network properties can be inferred from population measurements. However, this approach masks underlying temporal fluctuations of intracellular signalling events. We have inferred fundamental properties of the chemotaxis network from a noise analysis of behavioural variations in individual bacteria. Here we show that certain properties established by population measurements, such as adapted states, are not conserved at the single-cell level: for timescales ranging from seconds to several minutes, the behaviour of non-stimulated cells exhibit temporal variations much larger than the expected statistical fluctuations. We find that the signalling network itself causes this noise and identify the molecular events that produce it. Small changes in the concentration of one key network component suppress temporal behavioural variability, suggesting that such variability is a selected property of this adaptive system.

  2. Performance Analysis of Diversity-Controlled Multi-User Superposition Transmission for 5G Wireless Networks

    PubMed Central

    Yeom, Jeong Seon; Jung, Bang Chul; Jin, Hu

    2018-01-01

    In this paper, we propose a novel low-complexity multi-user superposition transmission (MUST) technique for 5G downlink networks, which allows multiple cell-edge users to be multiplexed with a single cell-center user. We call the proposed technique diversity-controlled MUST technique since the cell-center user enjoys the frequency diversity effect via signal repetition over multiple orthogonal frequency division multiplexing (OFDM) sub-carriers. We assume that a base station is equipped with a single antenna but users are equipped with multiple antennas. In addition, we assume that the quadrature phase shift keying (QPSK) modulation is used for users. We mathematically analyze the bit error rate (BER) of both cell-edge users and cell-center users, which is the first theoretical result in the literature to the best of our knowledge. The mathematical analysis is validated through extensive link-level simulations. PMID:29439413

  3. Performance Analysis of Diversity-Controlled Multi-User Superposition Transmission for 5G Wireless Networks.

    PubMed

    Yeom, Jeong Seon; Chu, Eunmi; Jung, Bang Chul; Jin, Hu

    2018-02-10

    In this paper, we propose a novel low-complexity multi-user superposition transmission (MUST) technique for 5G downlink networks, which allows multiple cell-edge users to be multiplexed with a single cell-center user. We call the proposed technique diversity-controlled MUST technique since the cell-center user enjoys the frequency diversity effect via signal repetition over multiple orthogonal frequency division multiplexing (OFDM) sub-carriers. We assume that a base station is equipped with a single antenna but users are equipped with multiple antennas. In addition, we assume that the quadrature phase shift keying (QPSK) modulation is used for users. We mathematically analyze the bit error rate (BER) of both cell-edge users and cell-center users, which is the first theoretical result in the literature to the best of our knowledge. The mathematical analysis is validated through extensive link-level simulations.

  4. Cellular network entropy as the energy potential in Waddington's differentiation landscape

    PubMed Central

    Banerji, Christopher R. S.; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X.; Teschendorff, Andrew E.

    2013-01-01

    Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape. PMID:24154593

  5. Centrality in earthquake multiplex networks

    NASA Astrophysics Data System (ADS)

    Lotfi, Nastaran; Darooneh, Amir Hossein; Rodrigues, Francisco A.

    2018-06-01

    Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a temporal network, described by a multiplex network, and characterize the evolution of the network structure in terms of the eigenvector centrality measure. We generalize previous works that considered the single layer representation of earthquake networks. Our results suggest that the multiplex representation captures better earthquake activity than methods based on single layer networks. We also verify that the regions with highest seismological activities in Iran and California can be identified from the network centrality analysis. The temporal modeling of seismic data provided here may open new possibilities for a better comprehension of the physics of earthquakes.

  6. Optimizing topological cascade resilience based on the structure of terrorist networks.

    PubMed

    Gutfraind, Alexander

    2010-11-10

    Complex socioeconomic networks such as information, finance and even terrorist networks need resilience to cascades--to prevent the failure of a single node from causing a far-reaching domino effect. We show that terrorist and guerrilla networks are uniquely cascade-resilient while maintaining high efficiency, but they become more vulnerable beyond a certain threshold. We also introduce an optimization method for constructing networks with high passive cascade resilience. The optimal networks are found to be based on cells, where each cell has a star topology. Counterintuitively, we find that there are conditions where networks should not be modified to stop cascades because doing so would come at a disproportionate loss of efficiency. Implementation of these findings can lead to more cascade-resilient networks in many diverse areas.

  7. Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

    PubMed Central

    Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

    2017-01-01

    Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

  8. Extracting grid cell characteristics from place cell inputs using non-negative principal component analysis

    PubMed Central

    Dordek, Yedidyah; Soudry, Daniel; Meir, Ron; Derdikman, Dori

    2016-01-01

    Many recent models study the downstream projection from grid cells to place cells, while recent data have pointed out the importance of the feedback projection. We thus asked how grid cells are affected by the nature of the input from the place cells. We propose a single-layer neural network with feedforward weights connecting place-like input cells to grid cell outputs. Place-to-grid weights are learned via a generalized Hebbian rule. The architecture of this network highly resembles neural networks used to perform Principal Component Analysis (PCA). Both numerical results and analytic considerations indicate that if the components of the feedforward neural network are non-negative, the output converges to a hexagonal lattice. Without the non-negativity constraint, the output converges to a square lattice. Consistent with experiments, grid spacing ratio between the first two consecutive modules is −1.4. Our results express a possible linkage between place cell to grid cell interactions and PCA. DOI: http://dx.doi.org/10.7554/eLife.10094.001 PMID:26952211

  9. A Single-Cell View of the BtsSR/YpdAB Pyruvate Sensing Network in Escherichia coli and Its Biological Relevance.

    PubMed

    Vilhena, Cláudia; Kaganovitch, Eugen; Shin, Jae Yen; Grünberger, Alexander; Behr, Stefan; Kristoficova, Ivica; Brameyer, Sophie; Kohlheyer, Dietrich; Jung, Kirsten

    2018-01-01

    Fluctuating environments and individual physiological diversity force bacteria to constantly adapt and optimize the uptake of substrates. We focus here on two very similar two-component systems (TCSs) of Escherichia coli belonging to the LytS/LytTR family: BtsS/BtsR (formerly YehU/YehT) and YpdA/YpdB. Both TCSs respond to extracellular pyruvate, albeit with different affinities, typically during postexponential growth, and each system regulates expression of a single transporter gene, yjiY and yhjX , respectively. To obtain insights into the biological significance of these TCSs, we analyzed the activation of the target promoters at the single-cell level. We found unimodal cell-to-cell variability; however, the degree of variance was strongly influenced by the available nutrients and differed between the two TCSs. We hypothesized that activation of either of the TCSs helps individual cells to replenish carbon resources. To test this hypothesis, we compared wild-type cells with the btsSR ypdAB mutant under two metabolically modulated conditions: protein overproduction and persister formation. Although all wild-type cells were able to overproduce green fluorescent protein (GFP), about half of the btsSR ypdAB population was unable to overexpress GFP. Moreover, the percentage of persister cells, which tolerate antibiotic stress, was significantly lower in the wild-type cells than in the btsSR ypdAB population. Hence, we suggest that the BtsS/BtsR and YpdA/YpdB network contributes to a balancing of the physiological state of all cells within a population. IMPORTANCE Histidine kinase/response regulator (HK/RR) systems enable bacteria to respond to environmental and physiological fluctuations. Escherichia coli and other members of the Enterobacteriaceae possess two similar LytS/LytTR-type HK/RRs, BtsS/BtsR (formerly YehU/YehT) and YpdA/YpdB, which form a functional network. Both systems are activated in response to external pyruvate, typically when cells face overflow metabolism during post-exponential growth. Single-cell analysis of the activation of their respective target genes yjiY and yhjX revealed cell-to-cell variability, and the range of variation was strongly influenced by externally available nutrients. Based on the phenotypic characterization of a btsSR ypdAB mutant compared to the parental strain, we suggest that this TCS network supports an optimization of the physiological state of the individuals within the population. Copyright © 2017 American Society for Microbiology.

  10. Continuous Attractor Network Model for Conjunctive Position-by-Velocity Tuning of Grid Cells

    PubMed Central

    Si, Bailu; Romani, Sandro; Tsodyks, Misha

    2014-01-01

    The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations. PMID:24743341

  11. Unidirectional signal propagation in primary neurons micropatterned at a single-cell resolution

    NASA Astrophysics Data System (ADS)

    Yamamoto, H.; Matsumura, R.; Takaoki, H.; Katsurabayashi, S.; Hirano-Iwata, A.; Niwano, M.

    2016-07-01

    The structure and connectivity of cultured neuronal networks can be controlled by using micropatterned surfaces. Here, we demonstrate that the direction of signal propagation can be precisely controlled at a single-cell resolution by growing primary neurons on micropatterns. To achieve this, we first examined the process by which axons develop and how synapses form in micropatterned primary neurons using immunocytochemistry. By aligning asymmetric micropatterns with a marginal gap, it was possible to pattern primary neurons with a directed polarization axis at the single-cell level. We then examined how synapses develop on micropatterned hippocampal neurons. Three types of micropatterns with different numbers of short paths for dendrite growth were compared. A normal development in synapse density was observed when micropatterns with three or more short paths were used. Finally, we performed double patch clamp recordings on micropatterned neurons to confirm that these synapses are indeed functional, and that the neuronal signal is transmitted unidirectionally in the intended orientation. This work provides a practical guideline for patterning single neurons to design functional neuronal networks in vitro with the direction of signal propagation being controlled.

  12. Single-Neuron NMDA Receptor Phenotype Influences Neuronal Rewiring and Reintegration following Traumatic Injury

    PubMed Central

    Patel, Tapan P.; Ventre, Scott C.; Geddes-Klein, Donna; Singh, Pallab K.

    2014-01-01

    Alterations in the activity of neural circuits are a common consequence of traumatic brain injury (TBI), but the relationship between single-neuron properties and the aggregate network behavior is not well understood. We recently reported that the GluN2B-containing NMDA receptors (NMDARs) are key in mediating mechanical forces during TBI, and that TBI produces a complex change in the functional connectivity of neuronal networks. Here, we evaluated whether cell-to-cell heterogeneity in the connectivity and aggregate contribution of GluN2B receptors to [Ca2+]i before injury influenced the functional rewiring, spontaneous activity, and network plasticity following injury using primary rat cortical dissociated neurons. We found that the functional connectivity of a neuron to its neighbors, combined with the relative influx of calcium through distinct NMDAR subtypes, together contributed to the individual neuronal response to trauma. Specifically, individual neurons whose [Ca2+]i oscillations were largely due to GluN2B NMDAR activation lost many of their functional targets 1 h following injury. In comparison, neurons with large GluN2A contribution or neurons with high functional connectivity both independently protected against injury-induced loss in connectivity. Mechanistically, we found that traumatic injury resulted in increased uncorrelated network activity, an effect linked to reduction of the voltage-sensitive Mg2+ block of GluN2B-containing NMDARs. This uncorrelated activation of GluN2B subtypes after injury significantly limited the potential for network remodeling in response to a plasticity stimulus. Together, our data suggest that two single-cell characteristics, the aggregate contribution of NMDAR subtypes and the number of functional connections, influence network structure following traumatic injury. PMID:24647941

  13. Cell Type-specific Intrinsic Perithreshold Oscillations in Hippocampal GABAergic Interneurons.

    PubMed

    Kang, Young-Jin; Lewis, Hannah Elisabeth Smashey; Young, Mason William; Govindaiah, Gubbi; Greenfield, Lazar John; Garcia-Rill, Edgar; Lee, Sang-Hun

    2018-04-15

    The hippocampus plays a critical role in learning, memory, and spatial processing through coordinated network activity including theta and gamma oscillations. Recent evidence suggests that hippocampal subregions (e.g., CA1) can generate these oscillations at the network level, at least in part, through GABAergic interneurons. However, it is unclear whether specific GABAergic interneurons generate intrinsic theta and/or gamma oscillations at the single-cell level. Since major types of CA1 interneurons (i.e., parvalbumin-positive basket cells (PVBCs), cannabinoid type 1 receptor-positive basket cells (CB 1 BCs), Schaffer collateral-associated cells (SCAs), neurogliaform cells and ivy cells) are thought to play key roles in network theta and gamma oscillations in the hippocampus, we tested the hypothesis that these cells generate intrinsic perithreshold oscillations at the single-cell level. We performed whole-cell patch-clamp recordings from GABAergic interneurons in the CA1 region of the mouse hippocampus in the presence of synaptic blockers to identify intrinsic perithreshold membrane potential oscillations. The majority of PVBCs (83%), but not the other interneuron subtypes, produced intrinsic perithreshold gamma oscillations if the membrane potential remained above -45 mV. In contrast, CB 1 BCs, SCAs, neurogliaform cells, ivy cells, and the remaining PVBCs (17%) produced intrinsic theta, but not gamma, oscillations. These oscillations were prevented by blockers of persistent sodium current. These data demonstrate that the major types of hippocampal interneurons produce distinct frequency bands of intrinsic perithreshold membrane oscillations. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

  14. Nonlinear microrheology and molecular imaging to map microscale deformations of entangled DNA networks

    NASA Astrophysics Data System (ADS)

    Wu, Tsai-Chin; Anderson, Rae

    We use active microrheology coupled to single-molecule fluorescence imaging to elucidate the microscale dynamics of entangled DNA. DNA naturally exists in a wide range of lengths and topologies, and is often confined in cell nucleui, forming highly concentrated and entangled biopolymer networks. Thus, DNA is the model polymer for understanding entangled polymer dynamics as well as the crowded environment of cells. These networks display complex viscoelastic properties that are not well understood, especially at the molecular-level and in response to nonlinear perturbations. Specifically, how microscopic stresses and strains propagate through entangled networks, and what molecular deformations lead to the network stress responses are unknown. To answer these important questions, we optically drive a microsphere through entangled DNA, perturbing the system far from equilibrium, while measuring the resistive force the DNA exerts on the bead during and after bead motion. We simultaneously image single fluorescent-labeled DNA molecules throughout the network to directly link the microscale stress response to molecular deformations. We characterize the deformation of the network from the molecular-level to the mesoscale, and map the stress propagation throughout the network. We further study the impact of DNA length (11 - 115 kbp) and topology (linear vs ring DNA) on deformation and propagation dynamics, exploring key nonlinear features such as tube dilation and power-law relaxation.

  15. Patterning of functional human astrocytes onto parylene-C/SiO2 substrates for the study of Ca2+ dynamics in astrocytic networks

    NASA Astrophysics Data System (ADS)

    Raos, B. J.; Simpson, M. C.; Doyle, C. S.; Murray, A. F.; Graham, E. S.; Unsworth, C. P.

    2018-06-01

    Objective. Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic knockout, are difficult to restrict to individual cells. The objective of this work is to develop cell-patterning techniques to physically manipulate astrocytic interactions to enable the study of Ca2+ in astrocytic networks. Approach. We investigate how an in vitro cell-patterning platform that utilizes geometric patterns of parylene-C on SiO2 can be used to physically isolate single astrocytes and small astrocytic networks. Main results. We report that single astrocytes are effectively isolated on 75  ×  75 µm square parylene nodes, whereas multi-cellular astrocytic networks are isolated on larger nodes, with the mean number of astrocytes per cluster increasing as a function of node size. Additionally, we report that astrocytes in small multi-cellular clusters exhibit spatio-temporal clustering of Ca2+ transients. Finally, we report that the frequency and regularity of Ca2+ transients was positively correlated with astrocyte connectivity. Significance. The significance of this work is to demonstrate how patterning hNT astrocytes replicates spatio-temporal clustering of Ca2+ signalling that is observed in vivo but not in dissociated in vitro cultures. We therefore highlight the importance of the structure of astrocytic networks in determining ensemble Ca2+ behaviour.

  16. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity.

    PubMed

    Dummer, Benjamin; Wieland, Stefan; Lindner, Benjamin

    2014-01-01

    A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i) a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii) a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, 2000) and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide an excellent approximations to the autocorrelation of spike trains in the recurrent network.

  17. From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods

    NASA Astrophysics Data System (ADS)

    Candia, Julián

    2013-03-01

    The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells.

  18. [Network structures in biological systems].

    PubMed

    Oleskin, A V

    2013-01-01

    Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

  19. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

    PubMed

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

  20. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

    PubMed Central

    Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

  1. Dynamical estimation of neuron and network properties III: network analysis using neuron spike times.

    PubMed

    Knowlton, Chris; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I

    2014-06-01

    Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.

  2. Investigating Cell Criticality

    NASA Astrophysics Data System (ADS)

    Serra, R.; Villani, M.; Damiani, C.; Graudenzi, A.; Ingrami, P.; Colacci, A.

    Random Boolean networks provide a way to give a precise meaning to the notion that living beings are in a critical state. Some phenomena which are observed in real biological systems (distribution of "avalanches" in gene knock-out experiments) can be modeled using random Boolean networks, and the results can be analytically proven to depend upon the Derrida parameter, which also determines whether the network is critical. By comparing observed and simulated data one can then draw inferences about the criticality of biological cells, although with some care because of the limited number of experimental observations. The relationship between the criticality of a single network and that of a set of interacting networks, which simulate a tissue or a bacterial colony, is also analyzed by computer simulations.

  3. Single-cell axotomy of cultured hippocampal neurons integrated in neuronal circuits.

    PubMed

    Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank

    2014-05-01

    An understanding of the molecular mechanisms of axon regeneration after injury is key for the development of potential therapies. Single-cell axotomy of dissociated neurons enables the study of the intrinsic regenerative capacities of injured axons. This protocol describes how to perform single-cell axotomy on dissociated hippocampal neurons containing synapses. Furthermore, to axotomize hippocampal neurons integrated in neuronal circuits, we describe how to set up coculture with a few fluorescently labeled neurons. This approach allows axotomy of single cells in a complex neuronal network and the observation of morphological and molecular changes during axon regeneration. Thus, single-cell axotomy of mature neurons is a valuable tool for gaining insights into cell intrinsic axon regeneration and the plasticity of neuronal polarity of mature neurons. Dissociation of the hippocampus and plating of hippocampal neurons takes ∼2 h. Neurons are then left to grow for 2 weeks, during which time they integrate into neuronal circuits. Subsequent axotomy takes 10 min per neuron and further imaging takes 10 min per neuron.

  4. Topological quantum computing with a very noisy network and local error rates approaching one percent.

    PubMed

    Nickerson, Naomi H; Li, Ying; Benjamin, Simon C

    2013-01-01

    A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems.

  5. Stochasticity in the signalling network of a model microbe

    NASA Astrophysics Data System (ADS)

    Bischofs, Ilka; Foley, Jonathan; Battenberg, Eric; Fontaine-Bodin, Lisa; Price, Gavin; Wolf, Denise; Arkin, Adam

    2007-03-01

    The soil dwelling bacterium Bacillus subtilis is an excellent model organism for studying stochastic stress response induction in an isoclonal population. Subjected to the same stressor cells undergo different cell fates, including sporulation, competence, degradative enzyme synthesis and motility. For example, under conditions of nutrient deprivation and high cell density only a portion of the cell population forms an endospore. Here we use a combined experimental and theoretical approach to study stochastic sporulation induction in Bacillus subtilis. Using several fluorescent reporter strains we apply time lapse fluorescent microscopy in combination with quantitative image analysis to study cell fate progression on a single cell basis and elucidate key noise generators in the underlying cellular network.

  6. Diffusion, capture and recycling of SCAR/WAVE and Arp2/3 complexes observed in cells by single-molecule imaging.

    PubMed

    Millius, Arthur; Watanabe, Naoki; Weiner, Orion D

    2012-03-01

    The SCAR/WAVE complex drives lamellipodium formation by enhancing actin nucleation by the Arp2/3 complex. Phosphoinositides and Rac activate the SCAR/WAVE complex, but how SCAR/WAVE and Arp2/3 complexes converge at sites of nucleation is unknown. We analyzed the single-molecule dynamics of WAVE2 and p40 (subunits of the SCAR/WAVE and Arp2/3 complexes, respectively) in XTC cells. We observed lateral diffusion of both proteins and captured the transition of p40 from diffusion to network incorporation. These results suggest that a diffusive 2D search facilitates binding of the Arp2/3 complex to actin filaments necessary for nucleation. After nucleation, the Arp2/3 complex integrates into the actin network and undergoes retrograde flow, which results in its broad distribution throughout the lamellipodium. By contrast, the SCAR/WAVE complex is more restricted to the cell periphery. However, with single-molecule imaging, we also observed WAVE2 molecules undergoing retrograde motion. WAVE2 and p40 have nearly identical speeds, lifetimes and sites of network incorporation. Inhibition of actin retrograde flow does not prevent WAVE2 association and disassociation with the membrane but does inhibit WAVE2 removal from the actin cortex. Our results suggest that membrane binding and diffusion expedites the recruitment of nucleation factors to a nucleation site independent of actin assembly, but after network incorporation, ongoing actin polymerization facilitates recycling of SCAR/WAVE and Arp2/3 complexes.

  7. Diffusion, capture and recycling of SCAR/WAVE and Arp2/3 complexes observed in cells by single-molecule imaging

    PubMed Central

    Millius, Arthur; Watanabe, Naoki; Weiner, Orion D.

    2012-01-01

    The SCAR/WAVE complex drives lamellipodium formation by enhancing actin nucleation by the Arp2/3 complex. Phosphoinositides and Rac activate the SCAR/WAVE complex, but how SCAR/WAVE and Arp2/3 complexes converge at sites of nucleation is unknown. We analyzed the single-molecule dynamics of WAVE2 and p40 (subunits of the SCAR/WAVE and Arp2/3 complexes, respectively) in XTC cells. We observed lateral diffusion of both proteins and captured the transition of p40 from diffusion to network incorporation. These results suggest that a diffusive 2D search facilitates binding of the Arp2/3 complex to actin filaments necessary for nucleation. After nucleation, the Arp2/3 complex integrates into the actin network and undergoes retrograde flow, which results in its broad distribution throughout the lamellipodium. By contrast, the SCAR/WAVE complex is more restricted to the cell periphery. However, with single-molecule imaging, we also observed WAVE2 molecules undergoing retrograde motion. WAVE2 and p40 have nearly identical speeds, lifetimes and sites of network incorporation. Inhibition of actin retrograde flow does not prevent WAVE2 association and disassociation with the membrane but does inhibit WAVE2 removal from the actin cortex. Our results suggest that membrane binding and diffusion expedites the recruitment of nucleation factors to a nucleation site independent of actin assembly, but after network incorporation, ongoing actin polymerization facilitates recycling of SCAR/WAVE and Arp2/3 complexes. PMID:22349699

  8. A Scalable Approach for Discovering Conserved Active Subnetworks across Species

    PubMed Central

    Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.

    2010-01-01

    Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309

  9. Large-scale imaging of cortical network activity with calcium indicators.

    PubMed

    Ikegaya, Yuji; Le Bon-Jego, Morgane; Yuste, Rafael

    2005-06-01

    Bulk loading of calcium indicators has provided a unique opportunity to reconstruct the activity of cortical networks with single-cell resolution. Here we describe the detailed methods of bulk loading of AM dyes we developed and have been improving for imaging with a spinning disk confocal microscope.

  10. Gene expression profiling of single cells on large-scale oligonucleotide arrays

    PubMed Central

    Hartmann, Claudia H.; Klein, Christoph A.

    2006-01-01

    Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717

  11. Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation

    PubMed Central

    Espinosa Angarica, Vladimir

    2016-01-01

    Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self‐renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation‐specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine. PMID:27321053

  12. A random access memory immune to single event upset using a T-Resistor

    DOEpatents

    Ochoa, A. Jr.

    1987-10-28

    In a random access memory cell, a resistance ''T'' decoupling network in each leg of the cell reduces random errors caused by the interaction of energetic ions with the semiconductor material forming the cell. The cell comprises two parallel legs each containing a series pair of complementary MOS transistors having a common gate connected to the node between the transistors of the opposite leg. The decoupling network in each leg is formed by a series pair of resistors between the transistors together with a third resistor interconnecting the junction between the pair of resistors and the gate of the transistor pair forming the opposite leg of the cell. 4 figs.

  13. Random access memory immune to single event upset using a T-resistor

    DOEpatents

    Ochoa, Jr., Agustin

    1989-01-01

    In a random access memory cell, a resistance "T" decoupling network in each leg of the cell reduces random errors caused by the interaction of energetic ions with the semiconductor material forming the cell. The cell comprises two parallel legs each containing a series pair of complementary MOS transistors having a common gate connected to the node between the transistors of the opposite leg. The decoupling network in each leg is formed by a series pair of resistors between the transistors together with a third resistor interconnecting the junction between the pair of resistors and the gate of the transistor pair forming the opposite leg of the cell.

  14. Unbiased Combinatorial Genomic Approaches to Identify Alternative Therapeutic Targets within the TSC Signaling Network

    DTIC Science & Technology

    2014-06-01

    Specifically, we combined the CRISPR genome editing system with a novel approach allowing efficient single cell cloning of Drosophila cells with the aim of...and culture these to produce cultures completely lacking wildtype sequence at the target locus. No robust methods existed to clone single Drosophila ...targeting all kinases and phosphatases (563 genes) in the Drosophila genome . 65 samples that displayed synthetic lethality (15 genes) or synthetic

  15. Modeling and controlling the two-phase dynamics of the p53 network: a Boolean network approach

    NASA Astrophysics Data System (ADS)

    Lin, Guo-Qiang; Ao, Bin; Chen, Jia-Wei; Wang, Wen-Xu; Di, Zeng-Ru

    2014-12-01

    Although much empirical evidence has demonstrated that p53 plays a key role in tumor suppression, the dynamics and function of the regulatory network centered on p53 have not yet been fully understood. Here, we develop a Boolean network model to reproduce the two-phase dynamics of the p53 network in response to DNA damage. In particular, we map the fates of cells into two types of Boolean attractors, and we find that the apoptosis attractor does not exist for minor DNA damage, reflecting that the cell is reparable. As the amount of DNA damage increases, the basin of the repair attractor shrinks, accompanied by the rising of the apoptosis attractor and the expansion of its basin, indicating that the cell becomes more irreparable with more DNA damage. For severe DNA damage, the repair attractor vanishes, and the apoptosis attractor dominates the state space, accounting for the exclusive fate of death. Based on the Boolean network model, we explore the significance of links, in terms of the sensitivity of the two-phase dynamics, to perturbing the weights of links and removing them. We find that the links are either critical or ordinary, rather than redundant. This implies that the p53 network is irreducible, but tolerant of small mutations at some ordinary links, and this can be interpreted with evolutionary theory. We further devised practical control schemes for steering the system into the apoptosis attractor in the presence of DNA damage by pinning the state of a single node or perturbing the weight of a single link. Our approach offers insights into understanding and controlling the p53 network, which is of paramount importance for medical treatment and genetic engineering.

  16. The single fgf receptor gene in the beetle Tribolium castaneum codes for two isoforms that integrate FGF8- and Branchless-dependent signals.

    PubMed

    Sharma, Rahul; Beer, Katharina; Iwanov, Katharina; Schmöhl, Felix; Beckmann, Paula Indigo; Schröder, Reinhard

    2015-06-15

    The precise regulation of cell-cell communication by numerous signal-transduction pathways is fundamental for many different processes during embryonic development. One important signalling pathway is the evolutionary conserved fibroblast-growth-factor (FGF)-pathway that controls processes like cell migration, axis specification and mesoderm formation in vertebrate and invertebrate animals. In the model insect Drosophila, the FGF ligand / receptor combinations of FGF8 (Pyramus and Thisbe) / Heartless (Htl) and Branchless (Bnl) / Breathless (Btl) are required for the migration of mesodermal cells and for the formation of the tracheal network respectively with both the receptors functioning independently of each other. However, only a single fgf-receptor gene (Tc-fgfr) has been identified in the genome of the beetle Tribolium. We therefore asked whether both the ligands Fgf8 and Bnl could transduce their signal through a common FGF-receptor in Tribolium. Indeed, we found that the function of the single Tc-fgfr gene is essential for mesoderm differentiation as well as for the formation of the tracheal network during early development. Ligand specific RNAi for Tc-fgf8 and Tc-bnl resulted in two distinct non-overlapping phenotypes of impaired mesoderm differentiation and abnormal formation of the tracheal network in Tc-fgf8- and Tc-bnl(RNAi) embryos respectively. We further show that the single Tc-fgfr gene encodes at least two different receptor isoforms that are generated through alternative splicing. We in addition demonstrate through exon-specific RNAi their distinct tissue-specific functions. Finally, we discuss the structure of the fgf-receptor gene from an evolutionary perspective. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Electrical coupling in ensembles of nonexcitable cells: modeling the spatial map of single cell potentials.

    PubMed

    Cervera, Javier; Manzanares, Jose Antonio; Mafe, Salvador

    2015-02-19

    We analyze the coupling of model nonexcitable (non-neural) cells assuming that the cell membrane potential is the basic individual property. We obtain this potential on the basis of the inward and outward rectifying voltage-gated channels characteristic of cell membranes. We concentrate on the electrical coupling of a cell ensemble rather than on the biochemical and mechanical characteristics of the individual cells, obtain the map of single cell potentials using simple assumptions, and suggest procedures to collectively modify this spatial map. The response of the cell ensemble to an external perturbation and the consequences of cell isolation, heterogeneity, and ensemble size are also analyzed. The results suggest that simple coupling mechanisms can be significant for the biophysical chemistry of model biomolecular ensembles. In particular, the spatiotemporal map of single cell potentials should be relevant for the uptake and distribution of charged nanoparticles over model cell ensembles and the collective properties of droplet networks incorporating protein ion channels inserted in lipid bilayers.

  18. Regulatory networks and connected components of the neutral space. A look at functional islands

    NASA Astrophysics Data System (ADS)

    Boldhaus, G.; Klemm, K.

    2010-09-01

    The functioning of a living cell is largely determined by the structure of its regulatory network, comprising non-linear interactions between regulatory genes. An important factor for the stability and evolvability of such regulatory systems is neutrality - typically a large number of alternative network structures give rise to the necessary dynamics. Here we study the discretized regulatory dynamics of the yeast cell cycle [Li et al., PNAS, 2004] and the set of networks capable of reproducing it, which we call functional. Among these, the empirical yeast wildtype network is close to optimal with respect to sparse wiring. Under point mutations, which establish or delete single interactions, the neutral space of functional networks is fragmented into ≈ 4.7 × 108 components. One of the smaller ones contains the wildtype network. On average, functional networks reachable from the wildtype by mutations are sparser, have higher noise resilience and fewer fixed point attractors as compared with networks outside of this wildtype component.

  19. Single-cell RNA-seq analysis unveils a prevalent epithelial/mesenchymal hybrid state during mouse organogenesis.

    PubMed

    Dong, Ji; Hu, Yuqiong; Fan, Xiaoying; Wu, Xinglong; Mao, Yunuo; Hu, Boqiang; Guo, Hongshan; Wen, Lu; Tang, Fuchou

    2018-03-14

    Organogenesis is crucial for proper organ formation during mammalian embryonic development. However, the similarities and shared features between different organs and the cellular heterogeneity during this process at single-cell resolution remain elusive. We perform single-cell RNA sequencing analysis of 1916 individual cells from eight organs and tissues of E9.5 to E11.5 mouse embryos, namely, the forebrain, hindbrain, skin, heart, somite, lung, liver, and intestine. Based on the regulatory activities rather than the expression patterns, all cells analyzed can be well classified into four major groups with epithelial, mesodermal, hematopoietic, and neuronal identities. For different organs within the same group, the similarities and differences of their features and developmental paths are revealed and reconstructed. We identify mutual interactions between epithelial and mesenchymal cells and detect epithelial cells with prevalent mesenchymal features during organogenesis, which are similar to the features of intermediate epithelial/mesenchymal cells during tumorigenesis. The comprehensive transcriptome at single-cell resolution profiled in our study paves the way for future mechanistic studies of the gene-regulatory networks governing mammalian organogenesis.

  20. Improved single-cell culture achieved using micromolding in capillaries technology coupled with poly (HEMA).

    PubMed

    Ye, Fang; Jiang, Jin; Chang, Honglong; Xie, Li; Deng, Jinjun; Ma, Zhibo; Yuan, Weizheng

    2015-07-01

    Cell studies at the single-cell level are becoming more and more critical for understanding the complex biological processes. Here, we present an optimization study investigating the positioning of single cells using micromolding in capillaries technology coupled with the cytophobic biomaterial poly (2-hydroxyethyl methacrylate) (poly (HEMA)). As a cytophobic biomaterial, poly (HEMA) was used to inhibit cells, whereas the glass was used as the substrate to provide a cell adhesive background. The poly (HEMA) chemical barrier was obtained using micromolding in capillaries, and the microchannel networks used for capillarity were easily achieved by reversibly bonding the polydimethylsiloxane mold and the glass. Finally, discrete cell adhesion regions were presented on the glass surface. This method is facile and low cost, and the reagents are commercially available. We validated the cytophobic abilities of the poly (HEMA), optimized the channel parameters for higher quality and more stable poly (HEMA) patterns by investigating the effects of changing the aspect ratio and the width of the microchannel on the poly (HEMA) grid pattern, and improved the single-cell occupancy by optimizing the dimensions of the cell adhesion regions.

  1. Accurate path integration in continuous attractor network models of grid cells.

    PubMed

    Burak, Yoram; Fiete, Ila R

    2009-02-01

    Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

  2. Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

    PubMed

    Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

    2010-01-01

    An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

  3. A Three-Dimensional Computational Model of Collagen Network Mechanics

    PubMed Central

    Lee, Byoungkoo; Zhou, Xin; Riching, Kristin; Eliceiri, Kevin W.; Keely, Patricia J.; Guelcher, Scott A.; Weaver, Alissa M.; Jiang, Yi

    2014-01-01

    Extracellular matrix (ECM) strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model) and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned). We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions. PMID:25386649

  4. Mean-field equations for neuronal networks with arbitrary degree distributions.

    PubMed

    Nykamp, Duane Q; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

    2017-04-01

    The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

  5. Mean-field equations for neuronal networks with arbitrary degree distributions

    NASA Astrophysics Data System (ADS)

    Nykamp, Duane Q.; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

    2017-04-01

    The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

  6. Trainable Gene Regulation Networks with Applications to Drosophila Pattern Formation

    NASA Technical Reports Server (NTRS)

    Mjolsness, Eric

    2000-01-01

    This chapter will very briefly introduce and review some computational experiments in using trainable gene regulation network models to simulate and understand selected episodes in the development of the fruit fly, Drosophila melanogaster. For details the reader is referred to the papers introduced below. It will then introduce a new gene regulation network model which can describe promoter-level substructure in gene regulation. As described in chapter 2, gene regulation may be thought of as a combination of cis-acting regulation by the extended promoter of a gene (including all regulatory sequences) by way of the transcription complex, and of trans-acting regulation by the transcription factor products of other genes. If we simplify the cis-action by using a phenomenological model which can be tuned to data, such as a unit or other small portion of an artificial neural network, then the full transacting interaction between multiple genes during development can be modelled as a larger network which can again be tuned or trained to data. The larger network will in general need to have recurrent (feedback) connections since at least some real gene regulation networks do. This is the basic modeling approach taken, which describes how a set of recurrent neural networks can be used as a modeling language for multiple developmental processes including gene regulation within a single cell, cell-cell communication, and cell division. Such network models have been called "gene circuits", "gene regulation networks", or "genetic regulatory networks", sometimes without distinguishing the models from the actual modeled systems.

  7. A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

    PubMed Central

    Lee, Esther J.

    2018-01-01

    Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals. PMID:29451874

  8. Mapping the physical network of cellular interactions.

    PubMed

    Boisset, Jean-Charles; Vivié, Judith; Grün, Dominic; Muraro, Mauro J; Lyubimova, Anna; van Oudenaarden, Alexander

    2018-05-21

    A cell's function is influenced by the environment, or niche, in which it resides. Studies of niches usually require assumptions about the cell types present, which impedes the discovery of new cell types or interactions. Here we describe ProximID, an approach for building a cellular network based on physical cell interaction and single-cell mRNA sequencing, and show that it can be used to discover new preferential cellular interactions without prior knowledge of component cell types. ProximID found specific interactions between megakaryocytes and mature neutrophils and between plasma cells and myeloblasts and/or promyelocytes (precursors of neutrophils) in mouse bone marrow, and it identified a Tac1 + enteroendocrine cell-Lgr5 + stem cell interaction in small intestine crypts. This strategy can be used to discover new niches or preferential interactions in a variety of organs.

  9. A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

    PubMed

    Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

    2013-01-01

    One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.

  10. Endothelial network formed with human dermal microvascular endothelial cells in autologous multicellular skin substitutes.

    PubMed

    Ponec, Maria; El Ghalbzouri, Abdoelwaheb; Dijkman, Remco; Kempenaar, Johanna; van der Pluijm, Gabri; Koolwijk, Pieter

    2004-01-01

    A human skin equivalent from a single skin biopsy harboring keratinocytes and melanocytes in the epidermal compartment, and fibroblasts and microvascular dermal endothelial cells in the dermal compartment was developed. The results of the study revealed that the nature of the extracellular matrix of the dermal compartments plays an important role in establishment of endothelial network in vitro. With rat-tail type I collagen matrices only lateral but not vertical expansion of endothelial networks was observed. In contrast, the presence of extracellular matrix of entirely human origin facilitated proper spatial organization of the endothelial network. Namely, when human dermal fibroblasts and microvascular endothelial cells were seeded on the bottom of an inert filter and subsequently epidermal cells were seeded on top of it, fibroblasts produced extracellular matrix throughout which numerous branched tubes were spreading three-dimensionally. Fibroblasts also facilitated the formation of basement membrane at the epidermal/matrix interface. Under all culture conditions, fully differentiated epidermis was formed with numerous melanocytes present in the basal epidermal cell layer. The results of the competitive RT-PCR revealed that both keratinocytes and fibroblasts expressed VEGF-A, -B, -C, aFGF and bFGF mRNA, whereas fibroblasts also expressed VEGF-D mRNA. At protein level, keratinocytes produced 10 times higher amounts of VEGF-A than fibroblasts did. The generation of multicellular skin equivalent from a single human skin biopsy will stimulate further developments for its application in the treatment of full-thickness skin defects. The potential development of biodegradable, biocompatible material suitable for these purposes is a great challenge for future research.

  11. Rapid one-step purification of single-cells encapsulated in alginate microcapsules from oil to aqueous phase using a hydrophobic filter paper: implications for single-cell experiments.

    PubMed

    Lee, Do-Hyun; Jang, Miran; Park, Je-Kyun

    2014-10-01

    By virtue of the biocompatibility and physical properties of hydrogel, picoliter-sized hydrogel microcapsules have been considered to be a biometric signature containing several features similar to that of encapsulated single cells, including phenotype, viability, and intracellular content. To maximize the experimental potential of encapsulating cells in hydrogel microcapsules, a method that enables efficient hydrogel microcapsule purification from oil is necessary. Current methods based on centrifugation for the conventional stepwise rinsing of oil, are slow and laborious and decrease the monodispersity and yield of the recovered hydrogel microcapsules. To remedy these shortcomings we have developed a simple one-step method to purify alginate microcapsules, containing a single live cell, from oil to aqueous phase. This method employs oil impregnation using a commercially available hydrophobic filter paper without multistep centrifugal purification and complicated microchannel networks. The oil-suspended alginate microcapsules encapsulating single cells from mammalian cancer cell lines (MCF-7, HepG2, and U937) and microorganisms (Chlorella vulgaris) were successfully exchanged to cell culture media by quick (~10 min) depletion of the surrounding oil phase without coalescence of neighboring microcapsules. Cell proliferation and high integrity of the microcapsules were also demonstrated by long-term incubation of microcapsules containing a single live cell. We expect that this method for the simple and rapid purification of encapsulated single-cell microcapsules will attain widespread adoption, assisting cell biologists and clinicians in the development of single-cell experiments. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Functional network inference of the suprachiasmatic nucleus

    PubMed Central

    Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel; St. John, Peter C.; Wang, Thomas J.; Bales, Benjamin B.; Doyle, Francis J.; Herzog, Erik D.; Petzold, Linda R.

    2016-01-01

    In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure. PMID:27044085

  13. The Potato virus X TGBp3 protein associates with the ER network for virus cell-to-cell movement

    NASA Technical Reports Server (NTRS)

    Krishnamurthy, Konduru; Heppler, Marty; Mitra, Ruchira; Blancaflor, Elison; Payton, Mark; Nelson, Richard S.; Verchot-Lubicz, Jeanmarie

    2003-01-01

    Potato virus X (PVX) TGBp3 is required for virus cell-to-cell movement. Cell-to-cell movement of TGBp3 was studied using biolistic bombardment of plasmids expressing GFP:TGBp3. TGBp3 moves between cells in Nicotiana benthamiana, but requires TGBp1 to move in N. tabacum leaves. In tobacco leaves GFP:TGBp3 accumulated in a pattern resembling the endoplasmic reticulum (ER). To determine if the ER network is important for GFP:TGBp3 and for PVX cell-to-cell movement, a single mutation inhibiting membrane binding of TGBp3 was introduced into GFP:TGBp3 and into PVX. This mutation disrupted movement of GFP:TGBp3 and PVX. Brefeldin A, which disrupts the ER network, also inhibited GFP:TGBp3 movement in both Nicotiana species. Two deletion mutations, that do not affect membrane binding, hindered GFP:TGBp3 and PVX cell-to-cell movement. Plasmids expressing GFP:TGBp2 and GFP:TGBp3 were bombarded to several other PVX hosts and neither protein moved between adjacent cells. In most hosts, TGBp2 or TGBp3 cannot move cell-to-cell.

  14. From grid cells to place cells with realistic field sizes

    PubMed Central

    2017-01-01

    While grid cells in the medial entorhinal cortex (MEC) of rodents have multiple, regularly arranged firing fields, place cells in the cornu ammonis (CA) regions of the hippocampus mostly have single spatial firing fields. Since there are extensive projections from MEC to the CA regions, many models have suggested that a feedforward network can transform grid cell firing into robust place cell firing. However, these models generate place fields that are consistently too small compared to those recorded in experiments. Here, we argue that it is implausible that grid cell activity alone can be transformed into place cells with robust place fields of realistic size in a feedforward network. We propose two solutions to this problem. Firstly, weakly spatially modulated cells, which are abundant throughout EC, provide input to downstream place cells along with grid cells. This simple model reproduces many place cell characteristics as well as results from lesion studies. Secondly, the recurrent connections between place cells in the CA3 network generate robust and realistic place fields. Both mechanisms could work in parallel in the hippocampal formation and this redundancy might account for the robustness of place cell responses to a range of disruptions of the hippocampal circuitry. PMID:28750005

  15. Phase Resetting Reveals Network Dynamics Underlying a Bacterial Cell Cycle

    PubMed Central

    Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R.; Scherer, Norbert F.

    2012-01-01

    Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS). PMID:23209388

  16. Phase resetting reveals network dynamics underlying a bacterial cell cycle.

    PubMed

    Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R; Scherer, Norbert F

    2012-01-01

    Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS).

  17. Biofunctionalized 3-D Carbon Nano-Network Platform for Enhanced Fibroblast Cell Adhesion

    NASA Astrophysics Data System (ADS)

    Chowdhury, A. K. M. Rezaul Haque; Tavangar, Amirhossein; Tan, Bo; Venkatakrishnan, Krishnan

    2017-03-01

    Carbon nanomaterials have been investigated for various biomedical applications. In most cases, however, these nanomaterials must be functionalized biologically or chemically due to their biological inertness or possible cytotoxicity. Here, we report the development of a new carbon nanomaterial with a bioactive phase that significantly promotes cell adhesion. We synthesize the bioactive phase by introducing self-assembled nanotopography and altered nano-chemistry to graphite substrates using ultrafast laser. To the best of our knowledge, this is the first time that such a cytophilic bio-carbon is developed in a single step without requiring subsequent biological/chemical treatments. By controlling the nano-network concentration and chemistry, we develop platforms with different degrees of cell cytophilicity. We study quantitatively and qualitatively the cell response to nano-network platforms with NIH-3T3 fibroblasts. The findings from the in vitro study indicate that the platforms possess excellent biocompatibility and promote cell adhesion considerably. The study of the cell morphology shows a healthy attachment of cells with a well-spread shape, overextended actin filaments, and morphological symmetry, which is indicative of a high cellular interaction with the nano-network. The developed nanomaterial possesses great biocompatibility and considerably stimulates cell adhesion and subsequent cell proliferation, thus offering a promising path toward engineering various biomedical devices.

  18. Cell-Type-Specific Predictive Network Yields Novel Insights into Mouse Embryonic Stem Cell Self-Renewal and Cell Fate

    PubMed Central

    Dowell, Karen G.; Simons, Allen K.; Wang, Zack Z.; Yun, Kyuson; Hibbs, Matthew A.

    2013-01-01

    Self-renewal, the ability of a stem cell to divide repeatedly while maintaining an undifferentiated state, is a defining characteristic of all stem cells. Here, we clarify the molecular foundations of mouse embryonic stem cell (mESC) self-renewal by applying a proven Bayesian network machine learning approach to integrate high-throughput data for protein function discovery. By focusing on a single stem-cell system, at a specific developmental stage, within the context of well-defined biological processes known to be active in that cell type, we produce a consensus predictive network that reflects biological reality more closely than those made by prior efforts using more generalized, context-independent methods. In addition, we show how machine learning efforts may be misled if the tissue specific role of mammalian proteins is not defined in the training set and circumscribed in the evidential data. For this study, we assembled an extensive compendium of mESC data: ∼2.2 million data points, collected from 60 different studies, under 992 conditions. We then integrated these data into a consensus mESC functional relationship network focused on biological processes associated with embryonic stem cell self-renewal and cell fate determination. Computational evaluations, literature validation, and analyses of predicted functional linkages show that our results are highly accurate and biologically relevant. Our mESC network predicts many novel players involved in self-renewal and serves as the foundation for future pluripotent stem cell studies. This network can be used by stem cell researchers (at http://StemSight.org) to explore hypotheses about gene function in the context of self-renewal and to prioritize genes of interest for experimental validation. PMID:23468881

  19. High-resolution Myogenic Lineage Mapping by Single-Cell Mass Cytometry

    PubMed Central

    Porpiglia, Ermelinda; Samusik, Nikolay; Ho, Andrew Tri Van; Cosgrove, Benjamin D.; Mai, Thach; Davis, Kara L.; Jager, Astraea; Nolan, Garry P.; Bendall, Sean C.; Fantl, Wendy J.; Blau, Helen M.

    2017-01-01

    Muscle regeneration is a dynamic process during which cell state and identity change over time. A major roadblock has been a lack of tools to resolve a myogenic progression in vivo. Here we capitalize on a transformative technology, single-cell mass cytometry (CyTOF), to identify in vivo skeletal muscle stem cell and previously unrecognized progenitor populations that precede differentiation. We discovered two cell surface markers, CD9 and CD104, whose combined expression enabled in vivo identification and prospective isolation of stem and progenitor cells. Data analysis using the X-shift algorithm paired with single-cell force directed layout visualization, defined a molecular signature of the activated stem cell state (CD44+/CD98+/MyoD+) and delineated a myogenic trajectory during recovery from acute muscle injury. Our studies uncover the dynamics of skeletal muscle regeneration in vivo and pave the way for the elucidation of the regulatory networks that underlie cell-state transitions in muscle diseases and aging. PMID:28414312

  20. A robust and tunable mitotic oscillator in artificial cells

    PubMed Central

    Wang, Shiyuan; Barnes, Patrick M; Liu, Xuwen; Xu, Haotian; Jin, Minjun; Liu, Allen P

    2018-01-01

    Single-cell analysis is pivotal to deciphering complex phenomena like heterogeneity, bistability, and asynchronous oscillations, where a population ensemble cannot represent individual behaviors. Bulk cell-free systems, despite having unique advantages of manipulation and characterization of biochemical networks, lack the essential single-cell information to understand a class of out-of-steady-state dynamics including cell cycles. Here, by encapsulating Xenopus egg extracts in water-in-oil microemulsions, we developed artificial cells that are adjustable in sizes and periods, sustain mitotic oscillations for over 30 cycles, and function in forms from the simplest cytoplasmic-only to the more complicated ones involving nuclear dynamics, mimicking real cells. Such innate flexibility and robustness make it key to studying clock properties like tunability and stochasticity. Our results also highlight energy as an important regulator of cell cycles. We demonstrate a simple, powerful, and likely generalizable strategy of integrating strengths of single-cell approaches into conventional in vitro systems to study complex clock functions. PMID:29620527

  1. Generation of murine induced pluripotent stem cells by using high-density distributed electrodes network.

    PubMed

    Lu, Ming-Yu; Li, Zhihong; Hwang, Shiaw-Min; Linju Yen, B; Lee, Gwo-Bin

    2015-09-01

    This study reports a robust method of gene transfection in a murine primary cell model by using a high-density electrodes network (HDEN). By demonstrating high cell viability after gene transfection and successful expression of transgenes including fluorescent proteins, the HDEN device shows great promise as a solution in which reprogramming efficiency using non-viral induction for generation of murine induced pluripotent stem cells (iPSCs) is optimized. High and steady transgene expression levels in host cells of iPSCs can be demonstrated using this method. Moreover, the HDEN device achieved successful gene transfection with a low voltage of less than 180 V while requiring relatively low cell numbers (less than 1.5 × 10(4) cells). The results are comparable to current conventional methods, demonstrating a reasonable fluorescent-plasmid transfection rate (42.4% in single transfection and 24.5% in triple transfection) and high cell viability of over 95%. The gene expression levels of each iPSC factor was measured to be over 10-fold higher than that reported in previous studies using a single mouse embryonic fibroblast cell. Our results demonstrate that the generation of iPSCs using HDEN transfection of plasmid DNA may be a feasible and safe alternative to using viral transfection methods in the near future.

  2. Design of robust flow processing networks with time-programmed responses

    NASA Astrophysics Data System (ADS)

    Kaluza, P.; Mikhailov, A. S.

    2012-04-01

    Can artificially designed networks reach the levels of robustness against local damage which are comparable with those of the biochemical networks of a living cell? We consider a simple model where the flow applied to an input node propagates through the network and arrives at different times to the output nodes, thus generating a pattern of coordinated responses. By using evolutionary optimization algorithms, functional networks - with required time-programmed responses - were constructed. Then, continuing the evolution, such networks were additionally optimized for robustness against deletion of individual nodes or links. In this manner, large ensembles of functional networks with different kinds of robustness were obtained, making statistical investigations and comparison of their structural properties possible. We have found that, generally, different architectures are needed for various kinds of robustness. The differences are statistically revealed, for example, in the Laplacian spectra of the respective graphs. On the other hand, motif distributions of robust networks do not differ from those of the merely functional networks; they are found to belong to the first Alon superfamily, the same as that of the gene transcription networks of single-cell organisms.

  3. A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network.

    PubMed

    Zhang, Daxing; Zhu, Yingmin; Pedrycz, Witold; Guo, Yongxian

    2016-05-18

    Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs.

  4. A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network

    PubMed Central

    Zhang, Daxing; Zhu, Yingmin; Pedrycz, Witold; Guo, Yongxian

    2016-01-01

    Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs. PMID:27213346

  5. Discreet charm of the GABAergic bourgeoisie: superconnected cells conduct developmental symphonies.

    PubMed

    Case, Marianne; Soltesz, Ivan

    2009-12-24

    In an exciting study in the December 4(th) issue of Science, Bonifazi and colleagues demonstrated the existence and importance of exceedingly rare but unusually richly connected cells in the developing hippocampus. Manipulating the activity of single GABAergic hub cells modulated network activity patterns, demonstrating their importance for coordinating synchronous activity. 2009 Elsevier Inc. All rights reserved.

  6. A linear programming approach to reconstructing subcellular structures from confocal images for automated generation of representative 3D cellular models.

    PubMed

    Wood, Scott T; Dean, Brian C; Dean, Delphine

    2013-04-01

    This paper presents a novel computer vision algorithm to analyze 3D stacks of confocal images of fluorescently stained single cells. The goal of the algorithm is to create representative in silico model structures that can be imported into finite element analysis software for mechanical characterization. Segmentation of cell and nucleus boundaries is accomplished via standard thresholding methods. Using novel linear programming methods, a representative actin stress fiber network is generated by computing a linear superposition of fibers having minimum discrepancy compared with an experimental 3D confocal image. Qualitative validation is performed through analysis of seven 3D confocal image stacks of adherent vascular smooth muscle cells (VSMCs) grown in 2D culture. The presented method is able to automatically generate 3D geometries of the cell's boundary, nucleus, and representative F-actin network based on standard cell microscopy data. These geometries can be used for direct importation and implementation in structural finite element models for analysis of the mechanics of a single cell to potentially speed discoveries in the fields of regenerative medicine, mechanobiology, and drug discovery. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. Imaging and reconstruction of cell cortex structures near the cell surface

    NASA Astrophysics Data System (ADS)

    Jin, Luhong; Zhou, Xiaoxu; Xiu, Peng; Luo, Wei; Huang, Yujia; Yu, Feng; Kuang, Cuifang; Sun, Yonghong; Liu, Xu; Xu, Yingke

    2017-11-01

    Total internal reflection fluorescence microscopy (TIRFM) provides high optical sectioning capability and superb signal-to-noise ratio for imaging of cell cortex structures. The development of multi-angle (MA)-TIRFM permits high axial resolution imaging and reconstruction of cellular structures near the cell surface. Cytoskeleton is composed of a network of filaments, which are important for maintenance of cell function. The high-resolution imaging and quantitative analysis of filament organization would contribute to our understanding of cytoskeleton regulation in cell. Here, we used a custom-developed MA-TIRFM setup, together with stochastic photobleaching and single molecule localization method, to enhance the lateral resolution of TIRFM imaging to about 100 nm. In addition, we proposed novel methods to perform filament segmentation and 3D reconstruction from MA-TIRFM images. Furthermore, we applied these methods to study the 3D localization of cortical actin and microtubule structures in U373 cancer cells. Our results showed that cortical actins localize ∼ 27 nm closer to the plasma membrane when compared with microtubules. We found that treatment of cells with chemotherapy drugs nocodazole and cytochalasin B disassembles cytoskeletal network and induces the reorganization of filaments towards the cell periphery. In summary, this study provides feasible approaches for 3D imaging and analyzing cell surface distribution of cytoskeletal network. Our established microscopy platform and image analysis toolkits would facilitate the study of cytoskeletal network in cells.

  8. An Ultrasensitive Bacterial Motor Revealed by Monitoring Signaling Proteins in Single Cells

    NASA Astrophysics Data System (ADS)

    Cluzel, Philippe; Surette, Michael; Leibler, Stanislas

    2000-03-01

    Understanding biology at the single-cell level requires simultaneous measurements of biochemical parameters and behavioral characteristics in individual cells. Here, the output of individual flagellar motors in Escherichia coli was measured as a function of the intracellular concentration of the chemotactic signaling protein. The concentration of this molecule, fused to green fluorescent protein, was monitored with fluorescence correlation spectroscopy. Motors from different bacteria exhibited an identical steep input-output relation, suggesting that they actively contribute to signal amplification in chemotaxis. This experimental approach can be extended to quantitative in vivo studies of other biochemical networks.

  9. A strain-cue hypothesis for biological network formation

    PubMed Central

    Cox, Brian N.

    2011-01-01

    The direction of migration of a cell invading a host population is assumed to be controlled by the magnitude of the strains in the host medium (cells plus extracellular matrix) that arise as the host medium deforms to accommodate the invader. The single assumption that invaders are cued by strains external to themselves is sufficient to generate network structures. The strain induced by a line of invaders is greatest at the extremity of the line and thus the strain field breaks symmetry, stabilizing branch formation. The strain cue also triggers sprouting from existing branches, with no further model assumption. Network characteristics depend primarily on the ratio of the rate of advance of the invaders to the rate of relaxation of the host cells after their initial deformation. Intra-cell mechanisms that govern these two rates control network morphology. The strain field that cues an individual invader is a collective response of the combined cell populations, involving the nearest 100 cells, to order of magnitude, to any invader. The mechanism does not rely on the pre-existence of the entire host medium prior to invasion; the host cells need only maintain a layer several cells thick around each invader. Consistent with recent experiments, networks result only from a strain cue that is based on strain magnitudes. Spatial strain gradients do not break symmetry and therefore cannot stabilize branch formation. The theory recreates most of the geometrical features of the nervous network in the mouse gut when the most influential adjustable parameter takes a value consistent with one inferred from human and mouse amelogenesis. Because of similarity in the guiding local strain fields, strain cues could also be a participating factor in the formation of vascular networks. PMID:20671068

  10. Pneumatic microfluidic cell compression device for high-throughput study of chondrocyte mechanobiology.

    PubMed

    Lee, Donghee; Erickson, Alek; You, Taesun; Dudley, Andrew T; Ryu, Sangjin

    2018-06-13

    Hyaline cartilage is a specialized type of connective tissue that lines many moveable joints (articular cartilage) and contributes to bone growth (growth plate cartilage). Hyaline cartilage is composed of a single cell type, the chondrocyte, which produces a unique hydrated matrix to resist compressive stress. Although compressive stress has profound effects on transcriptional networks and matrix biosynthesis in chondrocytes, mechanistic relationships between strain, signal transduction, cell metabolism, and matrix production remain superficial. Here, we describe development and validation of a polydimethylsiloxane (PDMS)-based pneumatic microfluidic cell compression device which generates multiple compression conditions in a single platform. The device contained an array of PDMS balloons of different sizes which were actuated by pressurized air, and the balloons compressed chondrocytes cells in alginate hydrogel constructs. Our characterization and testing of the device showed that the developed platform could compress chondrocytes with various magnitudes simultaneously with negligible effect on cell viability. Also, the device is compatible with live cell imaging to probe early effects of compressive stress, and it can be rapidly dismantled to facilitate molecular studies of compressive stress on transcriptional networks. Therefore, the proposed device will enhance the productivity of chondrocyte mechanobiology studies, and it can be applied to study mechanobiology of other cell types.

  11. SCOUP: a probabilistic model based on the Ornstein-Uhlenbeck process to analyze single-cell expression data during differentiation.

    PubMed

    Matsumoto, Hirotaka; Kiryu, Hisanori

    2016-06-08

    Single-cell technologies make it possible to quantify the comprehensive states of individual cells, and have the power to shed light on cellular differentiation in particular. Although several methods have been developed to fully analyze the single-cell expression data, there is still room for improvement in the analysis of differentiation. In this paper, we propose a novel method SCOUP to elucidate differentiation process. Unlike previous dimension reduction-based approaches, SCOUP describes the dynamics of gene expression throughout differentiation directly, including the degree of differentiation of a cell (in pseudo-time) and cell fate. SCOUP is superior to previous methods with respect to pseudo-time estimation, especially for single-cell RNA-seq. SCOUP also successfully estimates cell lineage more accurately than previous method, especially for cells at an early stage of bifurcation. In addition, SCOUP can be applied to various downstream analyses. As an example, we propose a novel correlation calculation method for elucidating regulatory relationships among genes. We apply this method to a single-cell RNA-seq data and detect a candidate of key regulator for differentiation and clusters in a correlation network which are not detected with conventional correlation analysis. We develop a stochastic process-based method SCOUP to analyze single-cell expression data throughout differentiation. SCOUP can estimate pseudo-time and cell lineage more accurately than previous methods. We also propose a novel correlation calculation method based on SCOUP. SCOUP is a promising approach for further single-cell analysis and available at https://github.com/hmatsu1226/SCOUP.

  12. Scaling of the surface vasculature on the human placenta

    NASA Astrophysics Data System (ADS)

    Leonard, A. S.; Lee, J.; Schubert, D.; Croen, L. A.; Fallin, M. D.; Newschaffer, C. J.; Walker, C. K.; Salafia, C. M.; Morgan, S. P.; Vvedensky, D. D.

    2017-10-01

    The networks of veins and arteries on the chorionic plate of the human placenta are analyzed in terms of Voronoi cells derived from these networks. Two groups of placentas from the United States are studied: a population cohort with no prescreening, and a cohort from newborns with an elevated risk of developing autistic spectrum disorder. Scaled distributions of the Voronoi cell areas in the two cohorts collapse onto a single distribution, indicating common mechanisms for the formation of the complete vasculatures, but which have different levels of activity in the two cohorts.

  13. Single Sublattice Endotaxial Phase Separation Driven by Charge Frustration in a Complex Oxide

    PubMed Central

    2013-01-01

    Complex transition-metal oxides are important functional materials in areas such as energy and information storage. The cubic ABO3 perovskite is an archetypal example of this class, formed by the occupation of small octahedral B-sites within an AO3 network defined by larger A cations. We show that introduction of chemically mismatched octahedral cations into a cubic perovskite oxide parent phase modifies structure and composition beyond the unit cell length scale on the B sublattice alone. This affords an endotaxial nanocomposite of two cubic perovskite phases with distinct properties. These locally B-site cation-ordered and -disordered phases share a single AO3 network and have enhanced stability against the formation of a competing hexagonal structure over the single-phase parent. Synergic integration of the distinct properties of these phases by the coherent interfaces of the composite produces solid oxide fuel cell cathode performance superior to that expected from the component phases in isolation. PMID:23750709

  14. Carbon nanotubes might improve neuronal performance by favouring electrical shortcuts.

    PubMed

    Cellot, Giada; Cilia, Emanuele; Cipollone, Sara; Rancic, Vladimir; Sucapane, Antonella; Giordani, Silvia; Gambazzi, Luca; Markram, Henry; Grandolfo, Micaela; Scaini, Denis; Gelain, Fabrizio; Casalis, Loredana; Prato, Maurizio; Giugliano, Michele; Ballerini, Laura

    2009-02-01

    Carbon nanotubes have been applied in several areas of nerve tissue engineering to probe and augment cell behaviour, to label and track subcellular components, and to study the growth and organization of neural networks. Recent reports show that nanotubes can sustain and promote neuronal electrical activity in networks of cultured cells, but the ways in which they affect cellular function are still poorly understood. Here, we show, using single-cell electrophysiology techniques, electron microscopy analysis and theoretical modelling, that nanotubes improve the responsiveness of neurons by forming tight contacts with the cell membranes that might favour electrical shortcuts between the proximal and distal compartments of the neuron. We propose the 'electrotonic hypothesis' to explain the physical interactions between the cell and nanotube, and the mechanisms of how carbon nanotubes might affect the collective electrical activity of cultured neuronal networks. These considerations offer a perspective that would allow us to predict or engineer interactions between neurons and carbon nanotubes.

  15. CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

    NASA Astrophysics Data System (ADS)

    Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

    2009-12-01

    Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

  16. Optimization Study of Hydrogen Gas Adsorption on Zig-zag Single-walled Carbon Nanotubes: The Artificial Neural Network Analysis

    NASA Astrophysics Data System (ADS)

    Nasruddin; Lestari, M.; Supriyadi; Sholahudin

    2018-03-01

    The use of hydrogen gas in fuel cell technology has a huge opportunity to be applied in upcoming vehicle technology. One of the most important problems in fuel cell technology is the hydrogen storage. The adsorption of hydrogen in carbon-based materials attracts a lot of attention because of its reliability. This study investigated the adsorption of hydrogen gas in Single-walled Carbon Nano Tubes (SWCNT) with chilarity of (0, 12), (0, 15), and (0, 18) to find the optimum chilarity. Artificial Neural Networks (ANN) can be used to predict the hydrogen storage capacity at different pressure and temperature conditions appropriately, using simulated series of data. The Artificial Neural Network is modeled as a predictor of the hydrogen adsorption capacity which provides solutions to some deficiencies in molecular dynamics (MD) simulations. In a previous study, ANN configurations have been developed for 77k, 233k, and 298k temperatures in hydrogen gas storage. To prepare this prediction, ANN is modeled to find out the configurations that exist in the set of training and validation of specified data selection, the distance between data, and the number of neurons that produce the smallest error. This configuration is needed to make an accurate artificial neural network. The configuration of neural network was then applied to this research. The neural network analysis results show that the best configuration of artificial neural network in hydrogen storage is at 233K temperature i.e. on SWCNT with chilarity of (0.12).

  17. Developmental Self-Construction and -Configuration of Functional Neocortical Neuronal Networks

    PubMed Central

    Bauer, Roman; Zubler, Frédéric; Pfister, Sabina; Hauri, Andreas; Pfeiffer, Michael; Muir, Dylan R.; Douglas, Rodney J.

    2014-01-01

    The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less systematic understanding of how these various processes play together in order to construct such functional networks. Here we make some steps toward such understanding by demonstrating through detailed simulations how a competitive co-operative (‘winner-take-all’, WTA) network architecture can arise by development from a single precursor cell. This precursor is granted a simplified gene regulatory network that directs cell mitosis, differentiation, migration, neurite outgrowth and synaptogenesis. Once initial axonal connection patterns are established, their synaptic weights undergo homeostatic unsupervised learning that is shaped by wave-like input patterns. We demonstrate how this autonomous genetically directed developmental sequence can give rise to self-calibrated WTA networks, and compare our simulation results with biological data. PMID:25474693

  18. Kinetic analyses of vasculogenesis inform mechanistic studies

    PubMed Central

    Winfree, Seth; Chu, Chenghao; Tu, Wanzhu; Blue, Emily K.; Gohn, Cassandra R.; Dunn, Kenneth W.

    2017-01-01

    Vasculogenesis is a complex process by which endothelial stem and progenitor cells undergo de novo vessel formation. Quantitative assessment of vasculogenesis is a central readout of endothelial progenitor cell functionality. However, current assays lack kinetic measurements. To address this issue, new approaches were developed to quantitatively assess in vitro endothelial colony-forming cell (ECFC) network formation in real time. Eight parameters of network structure were quantified using novel Kinetic Analysis of Vasculogenesis (KAV) software. KAV assessment of structure complexity identified two phases of network formation. This observation guided the development of additional vasculogenic readouts. A tissue cytometry approach was established to quantify the frequency and localization of dividing ECFCs. Additionally, Fiji TrackMate was used to quantify ECFC displacement and speed at the single-cell level during network formation. These novel approaches were then implemented to identify how intrauterine exposure to maternal diabetes mellitus (DM) impairs fetal ECFC vasculogenesis. Fetal ECFCs exposed to maternal DM form fewer initial network structures, which are not stable over time. Correlation analyses demonstrated that ECFC samples with greater division in branches form fewer closed network structures. Additionally, reductions in average ECFC movement over time decrease structural connectivity. Identification of these novel phenotypes utilizing the newly established methodologies provides evidence for the cellular mechanisms contributing to aberrant ECFC vasculogenesis. PMID:28100488

  19. A Self-organized MIMO-OFDM-based Cellular Network

    NASA Astrophysics Data System (ADS)

    Grünheid, Rainer; Fellenberg, Christian

    2012-05-01

    This paper presents a system proposal for a self-organized cellular network, which is based on the MIMO-OFDM transmission technique. Multicarrier transmission, combined with appropriate beamforming concepts, yields high bandwidth-efficiency and shows a robust behavior in multipath radio channels. Moreover, it provides a fine and tuneable granularity of space-time-frequency resources. Using a TDD approach and interference measurements in each cell, the Base Stations (BSs) decide autonomously which of the space-time-frequency resource blocks are allocated to the Mobile Terminals (MTs) in the cell, in order to fulfil certain Quality of Service (QoS) parameters. Since a synchronized Single Frequency Network (SFN), i.e., a re-use factor of one is applied, the resource blocks can be shared adaptively and flexibly among the cells, which is very advantageous in the case of a non-uniform MT distribution.

  20. Microwell Arrays for Studying Many Individual Cells

    NASA Technical Reports Server (NTRS)

    Folch, Albert; Kosar, Turgut Fettah

    2009-01-01

    "Laboratory-on-a-chip" devices that enable the simultaneous culturing and interrogation of many individual living cells have been invented. Each such device includes a silicon nitride-coated silicon chip containing an array of micromachined wells sized so that each well can contain one cell in contact or proximity with a patch clamp or other suitable single-cell-interrogating device. At the bottom of each well is a hole, typically 0.5 m wide, that connects the well with one of many channels in a microfluidic network formed in a layer of poly(dimethylsiloxane) on the underside of the chip. The microfluidic network makes it possible to address wells (and, thus, cells) individually to supply them with selected biochemicals. The microfluidic channels also provide electrical contact to the bottoms of the wells.

  1. Dissection of molecular assembly dynamics by tracking orientation and position of single molecules in live cells

    PubMed Central

    McQuilken, Molly; La Riviere, Patrick J.; Occhipinti, Patricia; Verma, Amitabh; Oldenbourg, Rudolf; Gladfelter, Amy S.; Tani, Tomomi

    2016-01-01

    Regulation of order, such as orientation and conformation, drives the function of most molecular assemblies in living cells but remains difficult to measure accurately through space and time. We built an instantaneous fluorescence polarization microscope, which simultaneously images position and orientation of fluorophores in living cells with single-molecule sensitivity and a time resolution of 100 ms. We developed image acquisition and analysis methods to track single particles that interact with higher-order assemblies of molecules. We tracked the fluctuations in position and orientation of molecules from the level of an ensemble of fluorophores down to single fluorophores. We tested our system in vitro using fluorescently labeled DNA and F-actin, in which the ensemble orientation of polarized fluorescence is known. We then tracked the orientation of sparsely labeled F-actin network at the leading edge of migrating human keratinocytes, revealing the anisotropic distribution of actin filaments relative to the local retrograde flow of the F-actin network. Additionally, we analyzed the position and orientation of septin-GFP molecules incorporated in septin bundles in growing hyphae of a filamentous fungus. Our data indicate that septin-GFP molecules undergo positional fluctuations within ∼350 nm of the binding site and angular fluctuations within ∼30° of the central orientation of the bundle. By reporting position and orientation of molecules while they form dynamic higher-order structures, our approach can provide insights into how micrometer-scale ordered assemblies emerge from nanoscale molecules in living cells. PMID:27679846

  2. Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

    NASA Astrophysics Data System (ADS)

    Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

    2018-06-01

    The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

  3. Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

    PubMed Central

    Manning, Cerys; Rattray, Magnus

    2017-01-01

    Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5’ LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package. PMID:28493880

  4. Evolution of Associative Learning in Chemical Networks

    PubMed Central

    McGregor, Simon; Vasas, Vera; Husbands, Phil; Fernando, Chrisantha

    2012-01-01

    Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ‘memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells. PMID:23133353

  5. Reducing uncertainties in energy dissipation measurements in atomic force spectroscopy of molecular networks and cell-adhesion studies.

    PubMed

    Biswas, Soma; Leitao, Samuel; Theillaud, Quentin; Erickson, Blake W; Fantner, Georg E

    2018-06-20

    Atomic force microscope (AFM) based single molecule force spectroscopy (SMFS) is a valuable tool in biophysics to investigate the ligand-receptor interactions, cell adhesion and cell mechanics. However, the force spectroscopy data analysis needs to be done carefully to extract the required quantitative parameters correctly. Especially the large number of molecules, commonly involved in complex networks formation; leads to very complicated force spectroscopy curves. One therefore, generally characterizes the total dissipated energy over a whole pulling cycle, as it is difficult to decompose the complex force curves into individual single molecule events. However, calculating the energy dissipation directly from the transformed force spectroscopy curves can lead to a significant over-estimation of the dissipated energy during a pulling experiment. The over-estimation of dissipated energy arises from the finite stiffness of the cantilever used for AFM based SMFS. Although this error can be significant, it is generally not compensated for. This can lead to significant misinterpretation of the energy dissipation (up to the order of 30%). In this paper, we show how in complex SMFS the excess dissipated energy caused by the stiffness of the cantilever can be identified and corrected using a high throughput algorithm. This algorithm is then applied to experimental results from molecular networks and cell-adhesion measurements to quantify the improvement in the estimation of the total energy dissipation.

  6. Functional network inference of the suprachiasmatic nucleus

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

    Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel

    2016-04-04

    In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data frommore » individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure.« less

  7. Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription–Translation (TX-TL) Systems

    PubMed Central

    2014-01-01

    RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on time scales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here, we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold tuning. Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo. PMID:24621257

  8. Networks of gold nanoparticles and bacteriophage as biological sensors and cell-targeting agents

    PubMed Central

    Souza, Glauco R.; Christianson, Dawn R.; Staquicini, Fernanda I.; Ozawa, Michael G.; Snyder, Evan Y.; Sidman, Richard L.; Miller, J. Houston; Arap, Wadih; Pasqualini, Renata

    2006-01-01

    Biological molecular assemblies are excellent models for the development of nanoengineered systems with desirable biomedical properties. Here we report an approach for fabrication of spontaneous, biologically active molecular networks consisting of bacteriophage (phage) directly assembled with gold (Au) nanoparticles (termed Au–phage). We show that when the phage are engineered so that each phage particle displays a peptide, such networks preserve the cell surface receptor binding and internalization attributes of the displayed peptide. The spontaneous organization of these targeted networks can be manipulated further by incorporation of imidazole (Au–phage–imid), which induces changes in fractal structure and near-infrared optical properties. The networks can be used as labels for enhanced fluorescence and dark-field microscopy, surface-enhanced Raman scattering detection, and near-infrared photon-to-heat conversion. Together, the physical and biological features within these targeted networks offer convenient multifunctional integration within a single entity with potential for nanotechnology-based biomedical applications. PMID:16434473

  9. Hydrogel Droplet Microfluidics for High-Throughput Single Molecule/Cell Analysis.

    PubMed

    Zhu, Zhi; Yang, Chaoyong James

    2017-01-17

    Heterogeneity among individual molecules and cells has posed significant challenges to traditional bulk assays, due to the assumption of average behavior, which would lose important biological information in heterogeneity and result in a misleading interpretation. Single molecule/cell analysis has become an important and emerging field in biological and biomedical research for insights into heterogeneity between large populations at high resolution. Compared with the ensemble bulk method, single molecule/cell analysis explores the information on time trajectories, conformational states, and interactions of individual molecules/cells, all key factors in the study of chemical and biological reaction pathways. Various powerful techniques have been developed for single molecule/cell analysis, including flow cytometry, atomic force microscopy, optical and magnetic tweezers, single-molecule fluorescence spectroscopy, and so forth. However, some of them have the low-throughput issue that has to analyze single molecules/cells one by one. Flow cytometry is a widely used high-throughput technique for single cell analysis but lacks the ability for intercellular interaction study and local environment control. Droplet microfluidics becomes attractive for single molecule/cell manipulation because single molecules/cells can be individually encased in monodisperse microdroplets, allowing high-throughput analysis and manipulation with precise control of the local environment. Moreover, hydrogels, cross-linked polymer networks that swell in the presence of water, have been introduced into droplet microfluidic systems as hydrogel droplet microfluidics. By replacing an aqueous phase with a monomer or polymer solution, hydrogel droplets can be generated on microfluidic chips for encapsulation of single molecules/cells according to the Poisson distribution. The sol-gel transition property endows the hydrogel droplets with new functionalities and diversified applications in single molecule/cell analysis. The hydrogel can act as a 3D cell culture matrix to mimic the extracellular environment for long-term single cell culture, which allows further heterogeneity study in proliferation, drug screening, and metastasis at the single-cell level. The sol-gel transition allows reactions in solution to be performed rapidly and efficiently with product storage in the gel for flexible downstream manipulation and analysis. More importantly, controllable sol-gel regulation provides a new way to maintain phenotype-genotype linkages in the hydrogel matrix for high throughput molecular evolution. In this Account, we will review the hydrogel droplet generation on microfluidics, single molecule/cell encapsulation in hydrogel droplets, as well as the progress made by our group and others in the application of hydrogel droplet microfluidics for single molecule/cell analysis, including single cell culture, single molecule/cell detection, single cell sequencing, and molecular evolution.

  10. On-Chip Cellomics: Constructive Understanding of Multicellular Network Using On-Chip Cellomics Technology

    NASA Astrophysics Data System (ADS)

    Yasuda, Kenji

    2012-08-01

    We have developed methods and systems of analyzing epigenetic information in cells to expand our understanding of how living systems are determined. Because cells are minimum units reflecting epigenetic information, which is considered to map the history of a parallel-processing recurrent network of biochemical reactions, their behaviors cannot be explained by considering only conventional deonucleotide (DNA) information-processing events. The role of epigenetic information on cells, which complements their genetic information, was inferred by comparing predictions from genetic information with cell behaviour observed under conditions chosen to reveal adaptation processes and community effects. A system of analyzing epigenetic information, on-chip cellomics technology, has been developed starting from the twin complementary viewpoints of cell regulation as an “algebraic” system (emphasis on temporal aspects) and as a “geometric” system (emphasis on spatial aspects) exploiting microfabrication technology and a reconstructive approach of cellular systems not only for single cell-based subjects such as Escherichia coli and macrophages but also for cellular networks like the community effect of cardiomyocytes and plasticity in neuronal networks. One of the most important contributions of this study was to be able to reconstruct the concept of a cell regulatory network from the “local” (molecules expressed at certain times and places) to the “global” (the cell as a viable, functioning system). Knowledge of epigenetic information, which we can control and change during cell lives, complements the genetic variety, and these two types of information are indispensable for living organisms. This new knowlege has the potential to be the basis of cell-based biological and medical fields such as those involving cell-based drug screening and the regeneration of organs from stem cells.

  11. Cell-ECM Interactions During Cancer Invasion

    NASA Astrophysics Data System (ADS)

    Jiang, Yi

    The extracellular matrix (ECM), a fibrous material that forms a network in a tissue, significantly affects many aspects of cellular behavior, including cell movement and proliferation. Transgenic mouse tumor studies indicate that excess collagen, a major component of ECM, enhances tumor formation and invasiveness. Clinically, tumor associated collagen signatures are strong markers for breast cancer survival. However, the underlying mechanisms are unclear since the properties of ECM are complex, with diverse structural and mechanical properties depending on various biophysical parameters. We have developed a three-dimensional elastic fiber network model, and parameterized it with in vitro collagen mechanics. Using this model, we study ECM remodeling as a result of local deformation and cell migration through the ECM as a network percolation problem. We have also developed a three-dimensional, multiscale model of cell migration and interaction with ECM. Our model reproduces quantitative single cell migration experiments. This model is a first step toward a fully biomechanical cell-matrix interaction model and may shed light on tumor associated collagen signatures in breast cancer. This work was partially supported by NIH-U01CA143069.

  12. FRET and BRET-based biosensors in live cell compound screens.

    PubMed

    Robinson, Katie Herbst; Yang, Jessica R; Zhang, Jin

    2014-01-01

    Live cell compound screening with genetically encoded fluorescence or bioluminescence-based biosensors offers a potentially powerful approach to identify novel regulators of a signaling event of interest. In particular, compound screening in living cells has the added benefit that the entire signaling network remains intact, and thus the screen is not just against a single molecule of interest but against any molecule within the signaling network that may modulate the distinct signaling event reported by the biosensor in use. Furthermore, only molecules that are cell permeable or act at cell surface receptors will be identified as "hits," thus reducing further optimization of the compound in terms of cell penetration. Here we discuss a detailed protocol for using genetically encoded biosensors in living cells in a 96-well format for the execution of high throughput compound screens and the identification of small molecules which modulate a signaling event of interest.

  13. Inference of RhoGAP/GTPase regulation using single-cell morphological data from a combinatorial RNAi screen.

    PubMed

    Nir, Oaz; Bakal, Chris; Perrimon, Norbert; Berger, Bonnie

    2010-03-01

    Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.

  14. Application of advanced cytometric and molecular technologies to minimal residual disease monitoring

    NASA Astrophysics Data System (ADS)

    Leary, James F.; He, Feng; Reece, Lisa M.

    2000-04-01

    Minimal residual disease monitoring presents a number of theoretical and practical challenges. Recently it has been possible to meet some of these challenges by combining a number of new advanced biotechnologies. To monitor the number of residual tumor cells requires complex cocktails of molecular probes that collectively provide sensitivities of detection on the order of one residual tumor cell per million total cells. Ultra-high-speed, multi parameter flow cytometry is capable of analyzing cells at rates in excess of 100,000 cells/sec. Residual tumor selection marker cocktails can be optimized by use of receiver operating characteristic analysis. New data minimizing techniques when combined with multi variate statistical or neural network classifications of tumor cells can more accurately predict residual tumor cell frequencies. The combination of these techniques can, under at least some circumstances, detect frequencies of tumor cells as low as one cell in a million with an accuracy of over 98 percent correct classification. Detection of mutations in tumor suppressor genes requires insolation of these rare tumor cells and single-cell DNA sequencing. Rare residual tumor cells can be isolated at single cell level by high-resolution single-cell cell sorting. Molecular characterization of tumor suppressor gene mutations can be accomplished using a combination of single- cell polymerase chain reaction amplification of specific gene sequences followed by TA cloning techniques and DNA sequencing. Mutations as small as a single base pair in a tumor suppressor gene of a single sorted tumor cell have been detected using these methods. Using new amplification procedures and DNA micro arrays it should be possible to extend the capabilities shown in this paper to screening of multiple DNA mutations in tumor suppressor and other genes on small numbers of sorted metastatic tumor cells.

  15. Emergence of Critical Behavior in β-Cell Network

    NASA Astrophysics Data System (ADS)

    Westacott, Matthew; Hraha, Thomas; McClatchey, Mason; Pozzoli, Marina; Benninger, Richard

    2014-03-01

    The β-cell is a cell type located in the Islet of Langerhans, a micro-organ of the pancreas which maintains glucose homeostasis through secretion of insulin. An electrophysiological process governing insulin release occurs through initial uptake of blood glucose and generation of ATP which inhibits the ATP sensitive potassium channel (K-ATP) causing membrane depolarization (activation). Neighboring β-cells are electrically coupled through gap junctions which allow passage of cationic molecules, creating a network of coupled electrical oscillators. Cells exhibiting hyperpolzarized (inactive) membrane potential affect behavior of neighboring cells by electrically suppressing their depolarization. Here we observe critical behavior between global active-inactive states by increasing the number of inactive elements with the K-ATP inhibitor Diazoxide and a tunable ATP insensitive transgenic mouse model. We show this behavior occurs due to from cell-cell coupling as mice lacking β-cell gap junctions show no critical behavior. Also, a computational β-cell model was expanded to construct a coupled β-cell network and we show this model replicates the critical behavior seen in-vitro.While electrical activity of single β-cells is well studied these data highlight a newly defined characteristic of their emergent multicellular behavior within the Islet of Langerhans and may elucidate pathophysiology of Diabetes due to mutations in the K-ATP channel.

  16. Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states

    NASA Astrophysics Data System (ADS)

    García-Morales, Vladimir; Manzanares, José A.; Mafe, Salvador

    2017-04-01

    We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ . This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

  17. Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states.

    PubMed

    García-Morales, Vladimir; Manzanares, José A; Mafe, Salvador

    2017-04-01

    We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

  18. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

    PubMed

    Suzuki, Harukazu; Forrest, Alistair R R; van Nimwegen, Erik; Daub, Carsten O; Balwierz, Piotr J; Irvine, Katharine M; Lassmann, Timo; Ravasi, Timothy; Hasegawa, Yuki; de Hoon, Michiel J L; Katayama, Shintaro; Schroder, Kate; Carninci, Piero; Tomaru, Yasuhiro; Kanamori-Katayama, Mutsumi; Kubosaki, Atsutaka; Akalin, Altuna; Ando, Yoshinari; Arner, Erik; Asada, Maki; Asahara, Hiroshi; Bailey, Timothy; Bajic, Vladimir B; Bauer, Denis; Beckhouse, Anthony G; Bertin, Nicolas; Björkegren, Johan; Brombacher, Frank; Bulger, Erika; Chalk, Alistair M; Chiba, Joe; Cloonan, Nicole; Dawe, Adam; Dostie, Josee; Engström, Pär G; Essack, Magbubah; Faulkner, Geoffrey J; Fink, J Lynn; Fredman, David; Fujimori, Ko; Furuno, Masaaki; Gojobori, Takashi; Gough, Julian; Grimmond, Sean M; Gustafsson, Mika; Hashimoto, Megumi; Hashimoto, Takehiro; Hatakeyama, Mariko; Heinzel, Susanne; Hide, Winston; Hofmann, Oliver; Hörnquist, Michael; Huminiecki, Lukasz; Ikeo, Kazuho; Imamoto, Naoko; Inoue, Satoshi; Inoue, Yusuke; Ishihara, Ryoko; Iwayanagi, Takao; Jacobsen, Anders; Kaur, Mandeep; Kawaji, Hideya; Kerr, Markus C; Kimura, Ryuichiro; Kimura, Syuhei; Kimura, Yasumasa; Kitano, Hiroaki; Koga, Hisashi; Kojima, Toshio; Kondo, Shinji; Konno, Takeshi; Krogh, Anders; Kruger, Adele; Kumar, Ajit; Lenhard, Boris; Lennartsson, Andreas; Lindow, Morten; Lizio, Marina; Macpherson, Cameron; Maeda, Norihiro; Maher, Christopher A; Maqungo, Monique; Mar, Jessica; Matigian, Nicholas A; Matsuda, Hideo; Mattick, John S; Meier, Stuart; Miyamoto, Sei; Miyamoto-Sato, Etsuko; Nakabayashi, Kazuhiko; Nakachi, Yutaka; Nakano, Mika; Nygaard, Sanne; Okayama, Toshitsugu; Okazaki, Yasushi; Okuda-Yabukami, Haruka; Orlando, Valerio; Otomo, Jun; Pachkov, Mikhail; Petrovsky, Nikolai; Plessy, Charles; Quackenbush, John; Radovanovic, Aleksandar; Rehli, Michael; Saito, Rintaro; Sandelin, Albin; Schmeier, Sebastian; Schönbach, Christian; Schwartz, Ariel S; Semple, Colin A; Sera, Miho; Severin, Jessica; Shirahige, Katsuhiko; Simons, Cas; St Laurent, George; Suzuki, Masanori; Suzuki, Takahiro; Sweet, Matthew J; Taft, Ryan J; Takeda, Shizu; Takenaka, Yoichi; Tan, Kai; Taylor, Martin S; Teasdale, Rohan D; Tegnér, Jesper; Teichmann, Sarah; Valen, Eivind; Wahlestedt, Claes; Waki, Kazunori; Waterhouse, Andrew; Wells, Christine A; Winther, Ole; Wu, Linda; Yamaguchi, Kazumi; Yanagawa, Hiroshi; Yasuda, Jun; Zavolan, Mihaela; Hume, David A; Arakawa, Takahiro; Fukuda, Shiro; Imamura, Kengo; Kai, Chikatoshi; Kaiho, Ai; Kawashima, Tsugumi; Kawazu, Chika; Kitazume, Yayoi; Kojima, Miki; Miura, Hisashi; Murakami, Kayoko; Murata, Mitsuyoshi; Ninomiya, Noriko; Nishiyori, Hiromi; Noma, Shohei; Ogawa, Chihiro; Sano, Takuma; Simon, Christophe; Tagami, Michihira; Takahashi, Yukari; Kawai, Jun; Hayashizaki, Yoshihide

    2009-05-01

    Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

  19. Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level.

    PubMed

    Bono, Jacopo; Clopath, Claudia

    2017-09-26

    Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.

  20. Engineering biosynthetic excitable tissues from unexcitable cells for electrophysiological and cell therapy studies.

    PubMed

    Kirkton, Robert D; Bursac, Nenad

    2011-01-01

    Patch-clamp recordings in single-cell expression systems have been traditionally used to study the function of ion channels. However, this experimental setting does not enable assessment of tissue-level function such as action potential (AP) conduction. Here we introduce a biosynthetic system that permits studies of both channel activity in single cells and electrical conduction in multicellular networks. We convert unexcitable somatic cells into an autonomous source of electrically excitable and conducting cells by stably expressing only three membrane channels. The specific roles that these expressed channels have on AP shape and conduction are revealed by different pharmacological and pacing protocols. Furthermore, we demonstrate that biosynthetic excitable cells and tissues can repair large conduction defects within primary 2- and 3-dimensional cardiac cell cultures. This approach enables novel studies of ion channel function in a reproducible tissue-level setting and may stimulate the development of new cell-based therapies for excitable tissue repair.

  1. A novel anti-alpha-fetoprotein single-chain variable fragment displays anti-tumor effects in HepG2 cells as a single agent or in combination with paclitaxel.

    PubMed

    Ji, Xiaonan; Shen, Yanli; Sun, Hao; Gao, Xiangdong

    2016-08-01

    Human hepatocellular carcinoma (HCC) has a high rate of tumor recurrence and metastasis, resulting in shortened survival time. The function of alpha-fetoprotein (AFP) as a regulatory factor in the growth of HCC cells has been well defined. The aim of this study was to investigate the use of a novel AFP-specific single-chain variable fragment that blocked AFP and inhibited HCC cell growth. The results indicated that the anti-AFP single-chain variable fragment (scFv) induced growth inhibition of AFP-expressing HCC cell lines in vitro through induction of G1 cell cycle arrest and apoptosis. The mechanism of apoptosis probably involved with blocking AFP internalization and regulation of the PTEN/PI3K/Akt signaling network. Moreover, the anti-AFP-scFv also effectively sensitized the HepG2 cells to paclitaxel (PTX) at a lower concentration. The combination effect of PTX and anti-AFP-scFv displayed a synergistic effect on HepG2 cells both in vitro and in vivo. Our results demonstrated that targeting AFP by specific antibodies has potential immunotherapeutic efficacy in human HCC.

  2. Effect of noise in intelligent cellular decision making.

    PubMed

    Bates, Russell; Blyuss, Oleg; Alsaedi, Ahmed; Zaikin, Alexey

    2015-01-01

    Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli.

  3. How Can We Treat Cancer Disease Not Cancer Cells?

    PubMed

    Kim, Kyu-Won; Lee, Su-Jae; Kim, Woo-Young; Seo, Ji Hae; Lee, Ho-Young

    2017-01-01

    Since molecular biology studies began, researches in biological science have centered on proteins and genes at molecular level of a single cell. Cancer research has also focused on various functions of proteins and genes that distinguish cancer cells from normal cells. Accordingly, most contemporary anticancer drugs have been developed to target abnormal characteristics of cancer cells. Despite the great advances in the development of anticancer drugs, vast majority of patients with advanced cancer have shown grim prognosis and high rate of relapse. To resolve this problem, we must reevaluate our focuses in current cancer research. Cancer should be considered as a systemic disease because cancer cells undergo a complex interaction with various surrounding cells in cancer tissue and spread to whole body through metastasis under the control of the systemic modulation. Human body relies on the cooperative interaction between various tissues and organs, and each organ performs its specialized function through tissue-specific cell networks. Therefore, investigation of the tumor-specific cell networks can provide novel strategy to overcome the limitation of current cancer research. This review presents the limitations of the current cancer research, emphasizing the necessity of studying tissue-specific cell network which could be a new perspective on treating cancer disease, not cancer cells.

  4. Critical high-dimensional state transitions in cell populations or why cancers follow the principle ``What does not kill me makes me stronger''

    NASA Astrophysics Data System (ADS)

    Huang, Sui

    Transitions between high-dimensional attractor states in the quasi-potential landscape of the gene regulatory network, induced by environmental perturbations and/or facilitated by mutational rewiring of the network, underlie cell phenotype switching in development as well as in cancer progression, including acquisition of drug-resistant phenotypes. Considering heterogeneous cell populations as statistical ensembles of cells, and single-cell resolution gene expression profiling of cell populations undergoing a cell phenotype shift allow us now to map the topography of the landscape and its distortion. From snapshots of single-cell expression patterns of a cell population measured during major transitions we compute a quantity that identifies symmetry-breaking destabilization of attractors (bifurcation) and concomitant dimension-reduction of the state space manifold (landscape distortion) which precede critical transitions to new attractor states. The model predicts, and we show experimentally, the almost inevitable generation of aberrant cells associated with such critical transitions in multi-attractor landscapes: therapeutic perturbations which seek to push cancer cells to the apoptotic state, almost always produce ``rebellious'' cells which move in the ``opposite direction'': instead of dying they become more stem-cell-like and malignant. We show experimentally that the inadvertent generation of more malignant cancer cells by therapy indeed results from transition of surviving (but stressed) cells into unforeseen attractor states and not simply from selection of inherently more resistant cells. Thus, cancer cells follow not so much Darwin, as generally thought (survival of the fittest), but rather Nietzsche (What does not kill me makes me stronger). Supported by NIH (NCI, NIGMS), Alberta Innovates.

  5. Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration

    PubMed Central

    Karunarathne, W. K. Ajith; Giri, Lopamudra; Patel, Anilkumar K.; Venkatesh, Kareenhalli V.; Gautam, N.

    2013-01-01

    There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein–coupled receptor network control of other cell behaviors. PMID:23569254

  6. Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration.

    PubMed

    Karunarathne, W K Ajith; Giri, Lopamudra; Patel, Anilkumar K; Venkatesh, Kareenhalli V; Gautam, N

    2013-04-23

    There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein-coupled receptor network control of other cell behaviors.

  7. Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists.

    PubMed

    Zhu, Xun; Wolfgruber, Thomas K; Tasato, Austin; Arisdakessian, Cédric; Garmire, David G; Garmire, Lana X

    2017-12-05

    Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

  8. Minimal Network Topologies for Signal Processing during Collective Cell Chemotaxis.

    PubMed

    Yue, Haicen; Camley, Brian A; Rappel, Wouter-Jan

    2018-06-19

    Cell-cell communication plays an important role in collective cell migration. However, it remains unclear how cells in a group cooperatively process external signals to determine the group's direction of motion. Although the topology of signaling pathways is vitally important in single-cell chemotaxis, the signaling topology for collective chemotaxis has not been systematically studied. Here, we combine mathematical analysis and simulations to find minimal network topologies for multicellular signal processing in collective chemotaxis. We focus on border cell cluster chemotaxis in the Drosophila egg chamber, in which responses to several experimental perturbations of the signaling network are known. Our minimal signaling network includes only four elements: a chemoattractant, the protein Rac (indicating cell activation), cell protrusion, and a hypothesized global factor responsible for cell-cell interaction. Experimental data on cell protrusion statistics allows us to systematically narrow the number of possible topologies from more than 40,000,000 to only six minimal topologies with six interactions between the four elements. This analysis does not require a specific functional form of the interactions, and only qualitative features are needed; it is thus robust to many modeling choices. Simulations of a stochastic biochemical model of border cell chemotaxis show that the qualitative selection procedure accurately determines which topologies are consistent with the experiment. We fit our model for all six proposed topologies; each produces results that are consistent with all experimentally available data. Finally, we suggest experiments to further discriminate possible pathway topologies. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  9. The influence of single bursts vs. single spikes at excitatory dendrodendritic synapses

    PubMed Central

    Masurkar, Arjun V.; Chen, Wei R.

    2015-01-01

    The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in-vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC–interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, vs. single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. PMID:22277089

  10. The mechanical properties and cytotoxicity of cell-laden double-network hydrogels based on photocrosslinkable gelatin and gellan gum biomacromolecules.

    PubMed

    Shin, Hyeongho; Olsen, Bradley D; Khademhosseini, Ali

    2012-04-01

    A major goal in the application of hydrogels for tissue engineering scaffolds, especially for load-bearing tissues such as cartilage, is to develop hydrogels with high mechanical strength. In this study, a double-network (DN) strategy was used to engineer strong hydrogels that can encapsulate cells. We improved upon previously studied double-network (DN) hydrogels by using a processing condition compatible with cell survival. The DN hydrogels were created by a two-step photocrosslinking using gellan gum methacrylate (GGMA) for the rigid and brittle first network, and gelatin methacrylamide (GelMA) for the soft and ductile second network. We controlled the degree of methacrylation of each polymer so that they obtain relevant mechanical properties as each network. The DN was formed by photocrosslinking the GGMA, diffusing GelMA into the first network, and photocrosslinking the GelMA to form the second network. The formation of the DN was examined by diffusion tests of the large GelMA molecules into the GGMA network, the resulting enhancement in the mechanical properties, and the difference in mechanical properties between GGMA/GelMA single networks (SN) and DNs. The resulting DN hydrogels exhibited the compressive failure stress of up to 6.9 MPa, which approaches the strength of cartilage. It was found that there is an optimal range of the crosslink density of the second network for high strength of DN hydrogels. DN hydrogels with a higher mass ratio of GelMA to GGMA exhibited higher strength, which shows promise in developing even stronger DN hydrogels in the future. Three dimensional (3D) encapsulation of NIH-3T3 fibroblasts and the following viability test showed the cell-compatibility of the DN formation process. Given the high strength and the ability to encapsulate cells, the DN hydrogels made from photocrosslinkable macromolecules could be useful for the regeneration of load-bearing tissues. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. The mechanical properties and cytotoxicity of cell-laden double-network hydrogels based on photocrosslinkable gelatin and gellan gum biomacromolecules

    PubMed Central

    Shin, Hyeongho; Olsen, Bradley D.; Khademhosseini, Ali

    2012-01-01

    A major goal in the application of hydrogels for tissue engineering scaffolds, especially for load-bearing tissues such as cartilage, is to develop hydrogels with high mechanical strength. In this study, a double-network (DN) strategy was used to engineer strong hydrogels that can encapsulate cells. We improved upon previously studied double-network (DN) hydrogels by using a processing condition compatible with cell survival. The DN hydrogels were created by a two-step photocrosslinking using gellan gum methacrylate (GGMA) for the rigid and brittle first network, and gelatin methacrylamide (GelMA) for the soft and ductile second network. We controlled the degree of methacrylation of each polymer so that they obtain relevant mechanical properties as each network. The DN was formed by photocrosslinking the GGMA, diffusing GelMA into the first network, and photocrosslinking the GelMA to form the second network. The formation of the DN was examined by diffusion tests of the large GelMA molecules into the GGMA network, the resulting enhancement in the mechanical properties, and the difference in mechanical properties between GGMA/GelMA single networks (SN) and DNs. The resulting DN hydrogels exhibited the compressive failure stress of up to 6.9 MPa, which approaches the strength of cartilage. It was found that there is an optimal range of the crosslink density of the second network for high strength of DN hydrogels. DN hydrogels with a higher mass ratio of GelMA to GGMA exhibited higher strength, which shows promise in developing even stronger DN hydrogels in the future. Three dimensional (3D) encapsulation of NIH-3T3 fibroblasts and the following viability test showed the cell-compatibility of the DN formation process. Given the high strength and the ability to encapsulate cells, the DN hydrogels made from photocrosslinkable macromolecules could be useful for the regeneration of load-bearing tissues. PMID:22265786

  12. A biochemically semi-detailed model of auxin-mediated vein formation in plant leaves.

    PubMed

    Roussel, Marc R; Slingerland, Martin J

    2012-09-01

    We present here a model intended to capture the biochemistry of vein formation in plant leaves. The model consists of three modules. Two of these modules, those describing auxin signaling and transport in plant cells, are biochemically detailed. We couple these modules to a simple model for PIN (auxin efflux carrier) protein localization based on an extracellular auxin sensor. We study the single-cell responses of this combined model in order to verify proper functioning of the modeled biochemical network. We then assemble a multicellular model from the single-cell building blocks. We find that the model can, under some conditions, generate files of polarized cells, but not true veins. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  13. Adhesion and migration of CHO cells on micropatterned single layer graphene

    NASA Astrophysics Data System (ADS)

    Keshavan, S.; Oropesa-Nuñez, R.; Diaspro, A.; Canale, C.; Dante, S.

    2017-06-01

    Cell patterning technology on single layer graphene (SLG) is a fairly new field that can find applications in tissue engineering and biomaterial/biosensors development. Recently, we have developed a simple and effective approach for the fabrication of patterned SLG substrates by laser micromachining, and we have successfully applied it for the obtainment of geometrically ordered neural networks. Here, we exploit the same approach to investigate the generalization of the cell response to the surface cues of the fabricated substrates and, contextually, to quantify cell adhesion on the different areas of the patterns. To attain this goal, we tested Chinese hamster ovary (CHO) cells on PDL-coated micropatterned SLG substrates and quantified the adhesion by using single cell force spectroscopy (SCFS). Our results indicate higher cell adhesion on PDL-SLG, and, consequently, an initial CHO cell accumulation on the graphene areas, confirming the neuronal behaviour observed previously; interestingly, at later time point in culture, cell migration was observed towards the adjacent SLG ablated regions, which resulted more favourable for cell proliferation. Therefore, our findings indicate that the mechanism of interaction with the surface cues offered by the micropatterned substrates is strictly cell-type dependent.

  14. Fungal networks shape dynamics of bacterial dispersal and community assembly in cheese rind microbiomes.

    PubMed

    Zhang, Yuanchen; Kastman, Erik K; Guasto, Jeffrey S; Wolfe, Benjamin E

    2018-01-23

    Most studies of bacterial motility have examined small-scale (micrometer-centimeter) cell dispersal in monocultures. However, bacteria live in multispecies communities, where interactions with other microbes may inhibit or facilitate dispersal. Here, we demonstrate that motile bacteria in cheese rind microbiomes use physical networks created by filamentous fungi for dispersal, and that these interactions can shape microbial community structure. Serratia proteamaculans and other motile cheese rind bacteria disperse on fungal networks by swimming in the liquid layers formed on fungal hyphae. RNA-sequencing, transposon mutagenesis, and comparative genomics identify potential genetic mechanisms, including flagella-mediated motility, that control bacterial dispersal on hyphae. By manipulating fungal networks in experimental communities, we demonstrate that fungal-mediated bacterial dispersal can shift cheese rind microbiome composition by promoting the growth of motile over non-motile community members. Our single-cell to whole-community systems approach highlights the interactive dynamics of bacterial motility in multispecies microbiomes.

  15. Eight types of stem cells in the life cycle of the moss Physcomitrella patens.

    PubMed

    Kofuji, Rumiko; Hasebe, Mitsuyasu

    2014-02-01

    Stem cells self-renew and produce cells that differentiate to become the source of the plant body. The moss Physcomitrella patens forms eight types of stem cells during its life cycle and serves as a useful model in which to explore the evolution of such cells. The common ancestor of land plants is inferred to have been haplontic and to have formed stem cells only in the gametophyte generation. A single stem cell would have been maintained in the ancestral gametophyte meristem, as occurs in extant basal land plants. During land plant evolution, stem cells diverged in the gametophyte generation to form different types of body parts, including the protonema and rhizoid filaments, leafy-shoot and thalloid gametophores, and gametangia formed in moss. A simplex meristem with a single stem cell was acquired in the sporophyte generation early in land plant evolution. Subsequently, sporophyte stem cells became multiple in the meristem and were elaborated further in seed plant lineages, although the evolutionary origin of niche cells, which maintain stem cells is unknown. Comparisons of gene regulatory networks are expected to give insights into the general mechanisms of stem cell formation and maintenance in land plants and provide information about their evolution. P. patens develops at least seven types of simplex meristem in the gametophyte and at least one type in the sporophyte generation and is a good material for regulatory network comparisons. In this review, we summarize recently revealed molecular mechanisms of stem cell initiation and maintenance in the moss. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. ATM encryption testing

    NASA Astrophysics Data System (ADS)

    Capell, Joyce; Deeth, David

    1996-01-01

    This paper describes why encryption was selected by Lockheed Martin Missiles & Space as the means for securing ATM networks. The ATM encryption testing program is part of an ATM network trial provided by Pacific Bell under the California Research Education Network (CalREN). The problem being addressed is the threat to data security which results when changing from a packet switched network infrastructure to a circuit switched ATM network backbone. As organizations move to high speed cell-based networks, there is a break down in the traditional security model which is designed to protect packet switched data networks from external attacks. This is due to the fact that most data security firewalls filter IP packets, restricting inbound and outbound protocols, e.g. ftp. ATM networks, based on cell-switching over virtual circuits, does not support this method for restricting access since the protocol information is not carried by each cell. ATM switches set up multiple virtual connections, thus there is no longer a single point of entry into the internal network. The problem is further complicated by the fact that ATM networks support high speed multi-media applications, including real time video and video teleconferencing which are incompatible with packet switched networks. The ability to restrict access to Lockheed Martin networks in support of both unclassified and classified communications is required before ATM network technology can be fully deployed. The Lockheed Martin CalREN ATM testbed provides the opportunity to test ATM encryption prototypes with actual applications to assess the viability of ATM encryption methodologies prior to installing large scale ATM networks. Two prototype ATM encryptors are being tested: (1) `MILKBUSH' a prototype encryptor developed by NSA for transmission of government classified data over ATM networks, and (2) a prototype ATM encryptor developed by Sandia National Labs in New Mexico, for the encryption of proprietary data.

  17. Multifunctional picoliter droplet manipulation platform and its application in single cell analysis.

    PubMed

    Gu, Shu-Qing; Zhang, Yun-Xia; Zhu, Ying; Du, Wen-Bin; Yao, Bo; Fang, Qun

    2011-10-01

    We developed an automated and multifunctional microfluidic platform based on DropLab to perform flexible generation and complex manipulations of picoliter-scale droplets. Multiple manipulations including precise droplet generation, sequential reagent merging, and multistep solid-phase extraction for picoliter-scale droplets could be achieved in the present platform. The system precision in generating picoliter-scale droplets was significantly improved by minimizing the thermo-induced fluctuation of flow rate. A novel droplet fusion technique based on the difference of droplet interfacial tensions was developed without the need of special microchannel networks or external devices. It enabled sequential addition of reagents to droplets on demand for multistep reactions. We also developed an effective picoliter-scale droplet splitting technique with magnetic actuation. The difficulty in phase separation of magnetic beads from picoliter-scale droplets due to the high interfacial tension was overcome using ferromagnetic particles to carry the magnetic beads to pass through the phase interface. With this technique, multistep solid-phase extraction was achieved among picoliter-scale droplets. The present platform had the ability to perform complex multistep manipulations to picoliter-scale droplets, which is particularly required for single cell analysis. Its utility and potentials in single cell analysis were preliminarily demonstrated in achieving high-efficiency single-cell encapsulation, enzyme activity assay at the single cell level, and especially, single cell DNA purification based on solid-phase extraction.

  18. Principles of Systems Biology, No. 29.

    PubMed

    2018-05-23

    This month: in silico labeling of microscopy images (Christiansen/Finkbeiner), single-cell lineage trees and data integration (Rajewsky, Satija), gene expression (Weinberger/Simpson, Tavazoie, Ameres/Zuber), and signalling networks (Mercer/Wollscheid, Fussenegger). Copyright © 2018. Published by Elsevier Inc.

  19. Linking macroscopic with microscopic neuroanatomy using synthetic neuronal populations.

    PubMed

    Schneider, Calvin J; Cuntz, Hermann; Soltesz, Ivan

    2014-10-01

    Dendritic morphology has been shown to have a dramatic impact on neuronal function. However, population features such as the inherent variability in dendritic morphology between cells belonging to the same neuronal type are often overlooked when studying computation in neural networks. While detailed models for morphology and electrophysiology exist for many types of single neurons, the role of detailed single cell morphology in the population has not been studied quantitatively or computationally. Here we use the structural context of the neural tissue in which dendritic trees exist to drive their generation in silico. We synthesize the entire population of dentate gyrus granule cells, the most numerous cell type in the hippocampus, by growing their dendritic trees within their characteristic dendritic fields bounded by the realistic structural context of (1) the granule cell layer that contains all somata and (2) the molecular layer that contains the dendritic forest. This process enables branching statistics to be linked to larger scale neuroanatomical features. We find large differences in dendritic total length and individual path length measures as a function of location in the dentate gyrus and of somatic depth in the granule cell layer. We also predict the number of unique granule cell dendrites invading a given volume in the molecular layer. This work enables the complete population-level study of morphological properties and provides a framework to develop complex and realistic neural network models.

  20. Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations

    PubMed Central

    Schneider, Calvin J.; Cuntz, Hermann; Soltesz, Ivan

    2014-01-01

    Dendritic morphology has been shown to have a dramatic impact on neuronal function. However, population features such as the inherent variability in dendritic morphology between cells belonging to the same neuronal type are often overlooked when studying computation in neural networks. While detailed models for morphology and electrophysiology exist for many types of single neurons, the role of detailed single cell morphology in the population has not been studied quantitatively or computationally. Here we use the structural context of the neural tissue in which dendritic trees exist to drive their generation in silico. We synthesize the entire population of dentate gyrus granule cells, the most numerous cell type in the hippocampus, by growing their dendritic trees within their characteristic dendritic fields bounded by the realistic structural context of (1) the granule cell layer that contains all somata and (2) the molecular layer that contains the dendritic forest. This process enables branching statistics to be linked to larger scale neuroanatomical features. We find large differences in dendritic total length and individual path length measures as a function of location in the dentate gyrus and of somatic depth in the granule cell layer. We also predict the number of unique granule cell dendrites invading a given volume in the molecular layer. This work enables the complete population-level study of morphological properties and provides a framework to develop complex and realistic neural network models. PMID:25340814

  1. C. elegans network biology: a beginning.

    PubMed Central

    Piano, Fabio; Gunsalus, Kristin C; Hill, David E; Vidal, Marc

    2006-01-01

    The architecture and dynamics of molecular networks can provide an understanding of complex biological processes complementary to that obtained from the in-depth study of single genes and proteins. With a completely sequenced and well-annotated genome, a fully characterized cell lineage, and powerful tools available to dissect development, Caenorhabditis elegans, among metazoans, provides an optimal system to bridge cellular and organismal biology with the global properties of macromolecular networks. This chapter considers omic technologies available for C. elegans to describe molecular networks--encompassing transcriptional and phenotypic profiling as well as physical interaction mapping--and discusses how their individual and integrated applications are paving the way for a network-level understanding of C. elegans biology. PMID:18050437

  2. A Mathematical Model to study the Dynamics of Epithelial Cellular Networks

    PubMed Central

    Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D.; Tomlin, Claire J.

    2013-01-01

    Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction). PMID:23221083

  3. From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer’s Disease

    PubMed Central

    Dulla, Chris G.; Coulter, Douglas A.; Ziburkus, Jokubas

    2015-01-01

    Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer’s disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. PMID:25948650

  4. From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer's Disease.

    PubMed

    Dulla, Chris G; Coulter, Douglas A; Ziburkus, Jokubas

    2016-06-01

    Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer's disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. © The Author(s) 2015.

  5. Single cell network profiling assay in bladder cancer.

    PubMed

    Covey, Todd M; Vira, Manish A; Westfall, Matt; Gulrajani, Michael; Cholankeril, Michelle; Okhunov, Zhamshid; Levey, Helen R; Marimpietri, Carol; Hawtin, Rachael; Fields, Scott Z; Cesano, Alessandra

    2013-04-01

    The aim of this study was to assess the feasibility of applying the single cell network profiling (SCNP) assay to the examination of signaling networks in epithelial cancer cells, using bladder washings from 29 bladder cancer (BC) and 15 nonbladder cancer (NC) subjects. This report describes the methods we developed to detect rare epithelial cells (within the cells we collected from bladder washings), distinguish cancer cells from normal epithelial cells, and reproducibly quantify signaling within these low frequency cancer cells. Specifically, antibodies against CD45, cytokeratin, EpCAM, and cleaved-PARP (cPARP) were used to differentiate nonapoptotic epithelial cells from leukocytes, while measurements of DNA content to determine aneuploidy (DAPI stain) allowed for distinction between tumor and normal epithelial cells. Signaling activity in the PI3K and MAPK pathways was assessed by measuring intracellular levels of p-AKT and p-ERK at baseline and in response to pathway modulation; 66% (N = 19) of BC samples and 27% (N = 4) of NC samples met the "evaluable" criteria, i.e., at least 400,000 total cells available upon sample receipt with >2% of cells showing an epithelial phenotype. The majority of epithelial cells detected in BC samples were nonapoptotic and all signaling data were generated from identified cPARP negative cells. In four of 19 BC samples but in none of the NC specimens, SCNP assay identified epithelial cancer cells with a quantifiable increase in epidermal growth factor-induced p-AKT and p-ERK levels. Furthermore, preincubation with the PI3K inhibitor GDC-0941 reduced or completely inhibited basal and epidermal growth factor-induced p-AKT but, as expected, had no effect on p-ERK levels. This study demonstrates the feasibility of applying SCNP assay using multiparametric flow cytometry to the functional characterization of rare, bladder cancer cells collected from bladder washing. Following assay standardization, this method could potentially serve as a tool for disease characterization and drug development in bladder cancer and other solid tumors. Copyright © 2013 International Society for Advancement of Cytometry.

  6. An integrated multi-electrode-optrode array for in vitro optogenetics

    PubMed Central

    Welkenhuysen, Marleen; Hoffman, Luis; Luo, Zhengxiang; De Proft, Anabel; Van den Haute, Chris; Baekelandt, Veerle; Debyser, Zeger; Gielen, Georges; Puers, Robert; Braeken, Dries

    2016-01-01

    Modulation of a group of cells or tissue needs to be very precise in order to exercise effective control over the cell population under investigation. Optogenetic tools have already demonstrated to be of great value in the study of neuronal circuits and in neuromodulation. Ideally, they should permit very accurate resolution, preferably down to the single cell level. Further, to address a spatially distributed sample, independently addressable multiple optical outputs should be present. In current techniques, at least one of these requirements is not fulfilled. In addition to this, it is interesting to directly monitor feedback of the modulation by electrical registration of the activity of the stimulated cells. Here, we present the fabrication and characterization of a fully integrated silicon-based multi-electrode-optrode array (MEOA) for in vitro optogenetics. We demonstrate that this device allows for artifact-free electrical recording. Moreover, the MEOA was used to reliably elicit spiking activity from ChR2-transduced neurons. Thanks to the single cell resolution stimulation capability, we could determine spatial and temporal activation patterns and spike latencies of the neuronal network. This integrated approach to multi-site combined optical stimulation and electrical recording significantly advances today’s tool set for neuroscientists in their search to unravel neuronal network dynamics. PMID:26832455

  7. Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

    PubMed

    Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

    2013-08-01

    Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  8. Evoking prescribed spike times in stochastic neurons

    NASA Astrophysics Data System (ADS)

    Doose, Jens; Lindner, Benjamin

    2017-09-01

    Single cell stimulation in vivo is a powerful tool to investigate the properties of single neurons and their functionality in neural networks. We present a method to determine a cell-specific stimulus that reliably evokes a prescribed spike train with high temporal precision of action potentials. We test the performance of this stimulus in simulations for two different stochastic neuron models. For a broad range of parameters and a neuron firing with intermediate firing rates (20-40 Hz) the reliability in evoking the prescribed spike train is close to its theoretical maximum that is mainly determined by the level of intrinsic noise.

  9. Simultaneous stability and sensitivity in model cortical networks is achieved through anti-correlations between the in- and out-degree of connectivity

    PubMed Central

    Vasquez, Juan C.; Houweling, Arthur R.; Tiesinga, Paul

    2013-01-01

    Neuronal networks in rodent barrel cortex are characterized by stable low baseline firing rates. However, they are sensitive to the action potentials of single neurons as suggested by recent single-cell stimulation experiments that reported quantifiable behavioral responses in response to short spike trains elicited in single neurons. Hence, these networks are stable against internally generated fluctuations in firing rate but at the same time remain sensitive to similarly-sized externally induced perturbations. We investigated stability and sensitivity in a simple recurrent network of stochastic binary neurons and determined numerically the effects of correlation between the number of afferent (“in-degree”) and efferent (“out-degree”) connections in neurons. The key advance reported in this work is that anti-correlation between in-/out-degree distributions increased the stability of the network in comparison to networks with no correlation or positive correlations, while being able to achieve the same level of sensitivity. The experimental characterization of degree distributions is difficult because all pre-synaptic and post-synaptic neurons have to be identified and counted. We explored whether the statistics of network motifs, which requires the characterization of connections between small subsets of neurons, could be used to detect evidence for degree anti-correlations. We find that the sample frequency of the 3-neuron “ring” motif (1→2→3→1), can be used to detect degree anti-correlation for sub-networks of size 30 using about 50 samples, which is of significance because the necessary measurements are achievable experimentally in the near future. Taken together, we hypothesize that barrel cortex networks exhibit degree anti-correlations and specific network motif statistics. PMID:24223550

  10. Resolving protein interactions and organization downstream the T cell antigen receptor using single-molecule localization microscopy: a review

    NASA Astrophysics Data System (ADS)

    Sherman, Eilon

    2016-06-01

    Signal transduction is mediated by heterogeneous and dynamic protein complexes. Such complexes play a critical role in diverse cell functions, with the important example of T cell activation. Biochemical studies of signalling complexes and their imaging by diffraction limited microscopy have resulted in an intricate network of interactions downstream the T cell antigen receptor (TCR). However, in spite of their crucial roles in T cell activation, much remains to be learned about these signalling complexes, including their heterogeneous contents and size distribution, their complex arrangements in the PM, and the molecular requirements for their formation. Here, we review how recent advancements in single molecule localization microscopy have helped to shed new light on the organization of signalling complexes in single molecule detail in intact T cells. From these studies emerges a picture where cells extensively employ hierarchical and dynamic patterns of nano-scale organization to control the local concentration of interacting molecular species. These patterns are suggested to play a critical role in cell decision making. The combination of SMLM with more traditional techniques is expected to continue and critically contribute to our understanding of multimolecular protein complexes and their significance to cell function.

  11. Focal Activation of Cells by Plasmon Resonance Assisted Optical Injection of Signaling Molecules

    PubMed Central

    2015-01-01

    Experimental methods for single cell intracellular delivery are essential for probing cell signaling dynamics within complex cellular networks, such as those making up the tumor microenvironment. Here, we show a quantitative and general method of interrogation of signaling pathways. We applied highly focused near-infrared laser light to optically inject gold-coated liposomes encapsulating bioactive molecules into single cells for focal activation of cell signaling. For this demonstration, we encapsulated either inositol trisphosphate (IP3), an endogenous cell signaling second messenger, or adenophostin A (AdA), a potent analogue of IP, within 100 nm gold-coated liposomes, and injected these gold-coated liposomes and their contents into the cytosol of single ovarian carcinoma cells to initiate calcium (Ca2+) release from intracellular stores. Upon optical injection of IP3 or AdA at doses above the activation threshold, we observed increases in cytosolic Ca2+ concentration within the injected cell initiating the propagation of a Ca2+ wave throughout nearby cells. As confirmed by octanol-induced inhibition, the intercellular Ca2+ wave traveled via gap junctions. Optical injection of gold-coated liposomes represents a quantitative method of focal activation of signaling cascades of broad interest in biomedical research. PMID:24877558

  12. ELECTRIC PHASE ANGLE OF CELL MEMBRANES

    PubMed Central

    Cole, Kenneth S.

    1932-01-01

    From the theory of an electric network containing any combination of resistances and a single variable impedance element having a constant phase angle independent of frequency, it is shown that the graph of the terminal series reactance against the resistance is an arc of a circle with the position of the center depending upon the phase angle of the variable element. If it be assumed that biological systems are equivalent to such a network, the hypotheses are supported at low and intermediate frequencies by data on red blood cells, muscle, nerve, and potato. For some tissues there is a marked divergence from the circle at high frequencies, which is not interpreted. PMID:19872673

  13. A π-π 3D network of tetranuclear μ2/μ3-carbonato Dy(III) bis-pyrazolylpyridine clusters showing single molecule magnetism features.

    PubMed

    Gass, Ian A; Moubaraki, Boujemaa; Langley, Stuart K; Batten, Stuart R; Murray, Keith S

    2012-02-18

    2,6-Di(pyrazole-3-yl)pyridine, 3-bpp, forms a porous (4(9)·6(6)) π-π mediated 3D network of trigonal pyramidal [Dy(III)(4)] carbonato-bridged complexes, with hexagonal channels comprising 54% of the unit cell volume, the material displaying slow magnetisation reversal. This journal is © The Royal Society of Chemistry 2012

  14. Simultaneous profiling of activity patterns in multiple neuronal subclasses.

    PubMed

    Parrish, R Ryley; Grady, John; Codadu, Neela K; Trevelyan, Andrew J; Racca, Claudia

    2018-06-01

    Neuronal networks typically comprise heterogeneous populations of neurons. A core objective when seeking to understand such networks, therefore, is to identify what roles these different neuronal classes play. Acquiring single cell electrophysiology data for multiple cell classes can prove to be a large and daunting task. Alternatively, Ca 2+ network imaging provides activity profiles of large numbers of neurons simultaneously, but without distinguishing between cell classes. We therefore developed a strategy for combining cellular electrophysiology, Ca 2+ network imaging, and immunohistochemistry to provide activity profiles for multiple cell classes at once. This involves cross-referencing easily identifiable landmarks between imaging of the live and fixed tissue, and then using custom MATLAB functions to realign the two imaging data sets, to correct for distortions of the tissue introduced by the fixation or immunohistochemical processing. We illustrate the methodology for analyses of activity profiles during epileptiform events recorded in mouse brain slices. We further demonstrate the activity profile of a population of parvalbumin-positive interneurons prior, during, and following a seizure-like event. Current approaches to Ca 2+ network imaging analyses are severely limited in their ability to subclassify neurons, and often rely on transgenic approaches to identify cell classes. In contrast, our methodology is a generic, affordable, and flexible technique to characterize neuronal behaviour with respect to classification based on morphological and neurochemical identity. We present a new approach for analysing Ca 2+ network imaging datasets, and use this to explore the parvalbumin-positive interneuron activity during epileptiform events. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Evolving gene regulation networks into cellular networks guiding adaptive behavior: an outline how single cells could have evolved into a centralized neurosensory system

    PubMed Central

    Fritzsch, Bernd; Jahan, Israt; Pan, Ning; Elliott, Karen L.

    2014-01-01

    Understanding the evolution of the neurosensory system of man, able to reflect on its own origin, is one of the major goals of comparative neurobiology. Details of the origin of neurosensory cells, their aggregation into central nervous systems and associated sensory organs, their localized patterning into remarkably different cell types aggregated into variably sized parts of the central nervous system begin to emerge. Insights at the cellular and molecular level begin to shed some light on the evolution of neurosensory cells, partially covered in this review. Molecular evidence suggests that high mobility group (HMG) proteins of pre-metazoans evolved into the definitive Sox [SRY (sex determining region Y)-box] genes used for neurosensory precursor specification in metazoans. Likewise, pre-metazoan basic helix-loop-helix (bHLH) genes evolved in metazoans into the group A bHLH genes dedicated to neurosensory differentiation in bilaterians. Available evidence suggests that the Sox and bHLH genes evolved a cross-regulatory network able to synchronize expansion of precursor populations and their subsequent differentiation into novel parts of the brain or sensory organs. Molecular evidence suggests metazoans evolved patterning gene networks early and not dedicated to neuronal development. Only later in evolution were these patterning gene networks tied into the increasing complexity of diffusible factors, many of which were already present in pre-metazoans, to drive local patterning events. It appears that the evolving molecular basis of neurosensory cell development may have led, in interaction with differentially expressed patterning genes, to local network modifications guiding unique specializations of neurosensory cells into sensory organs and various areas of the central nervous system. PMID:25416504

  16. Evolving gene regulatory networks into cellular networks guiding adaptive behavior: an outline how single cells could have evolved into a centralized neurosensory system.

    PubMed

    Fritzsch, Bernd; Jahan, Israt; Pan, Ning; Elliott, Karen L

    2015-01-01

    Understanding the evolution of the neurosensory system of man, able to reflect on its own origin, is one of the major goals of comparative neurobiology. Details of the origin of neurosensory cells, their aggregation into central nervous systems and associated sensory organs and their localized patterning leading to remarkably different cell types aggregated into variably sized parts of the central nervous system have begun to emerge. Insights at the cellular and molecular level have begun to shed some light on the evolution of neurosensory cells, partially covered in this review. Molecular evidence suggests that high mobility group (HMG) proteins of pre-metazoans evolved into the definitive Sox [SRY (sex determining region Y)-box] genes used for neurosensory precursor specification in metazoans. Likewise, pre-metazoan basic helix-loop-helix (bHLH) genes evolved in metazoans into the group A bHLH genes dedicated to neurosensory differentiation in bilaterians. Available evidence suggests that the Sox and bHLH genes evolved a cross-regulatory network able to synchronize expansion of precursor populations and their subsequent differentiation into novel parts of the brain or sensory organs. Molecular evidence suggests metazoans evolved patterning gene networks early, which were not dedicated to neuronal development. Only later in evolution were these patterning gene networks tied into the increasing complexity of diffusible factors, many of which were already present in pre-metazoans, to drive local patterning events. It appears that the evolving molecular basis of neurosensory cell development may have led, in interaction with differentially expressed patterning genes, to local network modifications guiding unique specializations of neurosensory cells into sensory organs and various areas of the central nervous system.

  17. Molecular Programs Underlying Asymmetric Stem Cell Division and Their Disruption in Malignancy.

    PubMed

    Mukherjee, Subhas; Brat, Daniel J

    2017-01-01

    Asymmetric division of stem cells is a highly conserved and tightly regulated process by which a single stem cell produces two unequal daughter cells. One retains its stem cell identity while the other becomes specialized through a differentiation program and loses stem cell properties. Coordinating these events requires control over numerous intra- and extracellular biological processes and signaling networks. In the initial stages, critical events include the compartmentalization of fate determining proteins within the mother cell and their subsequent passage to the appropriate daughter cell in order to direct their destiny. Disturbance of these events results in an altered dynamic of self-renewing and differentiation within the cell population, which is highly relevant to the growth and progression of cancer. Other critical events include proper asymmetric spindle assembly, extrinsic regulation through micro-environmental cues, and non-canonical signaling networks that impact cell division and fate determination. In this review, we discuss mechanisms that maintain the delicate balance of asymmetric cell division in normal tissues and describe the current understanding how some of these mechanisms are deregulated in cancer.

  18. Interplay between population firing stability and single neuron dynamics in hippocampal networks

    PubMed Central

    Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna

    2015-01-01

    Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699

  19. A standalone perfusion platform for drug testing and target validation in micro-vessel networks

    PubMed Central

    Zhang, Boyang; Peticone, Carlotta; Murthy, Shashi K.; Radisic, Milica

    2013-01-01

    Studying the effects of pharmacological agents on human endothelium includes the routine use of cell monolayers cultivated in multi-well plates. This configuration fails to recapitulate the complex architecture of vascular networks in vivo and does not capture the relationship between shear stress (i.e. flow) experienced by the cells and dose of the applied pharmacological agents. Microfluidic platforms have been applied extensively to create vascular systems in vitro; however, they rely on bulky external hardware to operate, which hinders the wide application of microfluidic chips by non-microfluidic experts. Here, we have developed a standalone perfusion platform where multiple devices were perfused at a time with a single miniaturized peristaltic pump. Using the platform, multiple micro-vessel networks, that contained three levels of branching structures, were created by culturing endothelial cells within circular micro-channel networks mimicking the geometrical configuration of natural blood vessels. To demonstrate the feasibility of our platform for drug testing and validation assays, a drug induced nitric oxide assay was performed on the engineered micro-vessel network using a panel of vaso-active drugs (acetylcholine, phenylephrine, atorvastatin, and sildenafil), showing both flow and drug dose dependent responses. The interactive effects between flow and drug dose for sildenafil could not be captured by a simple straight rectangular channel coated with endothelial cells, but it was captured in a more physiological branching circular network. A monocyte adhesion assay was also demonstrated with and without stimulation by an inflammatory cytokine, tumor necrosis factor-α. PMID:24404058

  20. Network Modeling of MDM2 Inhibitor-Oxaliplatin Combination Reveals Biological Synergy in wt-p53 solid tumors

    PubMed Central

    Azmi, Asfar S.; Banerjee, Sanjeev; Ali, Shadan; Wang, Zhiwei; Bao, Bin; Beck, Frances W.J.; Maitah, Main; Choi, Minsig; Shields, Tony F.; Philip, Philip A.; Sarkar, Fazlul H.; Mohammad, Ramzi M.

    2011-01-01

    Earlier we had shown that the MDM2 inhibitor (MI-219) belonging to the spiro-oxindole family can synergistically enhance the efficacy of platinum chemotherapeutics leading to 50% tumor free survival in a genetically complex pancreatic ductal adenocarcinoma (PDAC) xenograft model. In this report, we have taken a systems and network modeling approach in order to understand central mechanisms behind MI219-oxaliplatin synergy with validation in PDAC, colon and breast cancer cell lines. Microarray profiling of drug treatments (MI-219, oxaliplatin or their combination) in capan-2 cells reveal a similar unique set of gene alterations that is duplicated in other solid tumor cells. As single agent, MI-219 or oxaliplatin induced alterations in 48 and 761 genes respectively. The combination treatment resulted in 767 gene alterations with emergence of 286 synergy unique genes. Ingenuity network modeling of combination and synergy unique genes showed the crucial role of five key local networks CREB, CARF, EGR1, NF-kB and E Cadherin. The network signatures were validated at the protein level in all three cell lines. Individually silencing central nodes in these five hubs resulted in abrogation of MI-219-oxaliplatin activity confirming their critical role in aiding p53 mediated apoptotic response. We anticipate that our MI219-oxaliplatin network blueprints can be clinically translated in the rationale design and application of this unique therapeutic combination in a genetically pre-defined subset of patients. PMID:21623005

  1. Highly ordered large-scale neuronal networks of individual cells - toward single cell to 3D nanowire intracellular interfaces.

    PubMed

    Kwiat, Moria; Elnathan, Roey; Pevzner, Alexander; Peretz, Asher; Barak, Boaz; Peretz, Hagit; Ducobni, Tamir; Stein, Daniel; Mittelman, Leonid; Ashery, Uri; Patolsky, Fernando

    2012-07-25

    The use of artificial, prepatterned neuronal networks in vitro is a promising approach for studying the development and dynamics of small neural systems in order to understand the basic functionality of neurons and later on of the brain. The present work presents a high fidelity and robust procedure for controlling neuronal growth on substrates such as silicon wafers and glass, enabling us to obtain mature and durable neural networks of individual cells at designed geometries. It offers several advantages compared to other related techniques that have been reported in recent years mainly because of its high yield and reproducibility. The procedure is based on surface chemistry that allows the formation of functional, tailormade neural architectures with a micrometer high-resolution partition, that has the ability to promote or repel cells attachment. The main achievements of this work are deemed to be the creation of a large scale neuronal network at low density down to individual cells, that develop intact typical neurites and synapses without any glia-supportive cells straight from the plating stage and with a relatively long term survival rate, up to 4 weeks. An important application of this method is its use on 3D nanopillars and 3D nanowire-device arrays, enabling not only the cell bodies, but also their neurites to be positioned directly on electrical devices and grow with registration to the recording elements underneath.

  2. Engineering biosynthetic excitable tissues from unexcitable cells for electrophysiological and cell therapy studies

    PubMed Central

    Kirkton, Robert D.; Bursac, Nenad

    2012-01-01

    Patch-clamp recordings in single-cell expression systems have been traditionally used to study the function of ion channels. However, this experimental setting does not enable assessment of tissue-level function such as action potential (AP) conduction. Here we introduce a biosynthetic system that permits studies of both channel activity in single cells and electrical conduction in multicellular networks. We convert unexcitable somatic cells into an autonomous source of electrically excitable and conducting cells by stably expressing only three membrane channels. The specific roles that these expressed channels have on AP shape and conduction are revealed by different pharmacological and pacing protocols. Furthermore, we demonstrate that biosynthetic excitable cells and tissues can repair large conduction defects within primary 2- and 3-dimensional cardiac cell cultures. This approach enables novel studies of ion channel function in a reproducible tissue-level setting and may stimulate the development of new cell-based therapies for excitable tissue repair. PMID:21556054

  3. The influence of single bursts versus single spikes at excitatory dendrodendritic synapses.

    PubMed

    Masurkar, Arjun V; Chen, Wei R

    2012-02-01

    The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC -interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, versus single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  4. Gene networks and developmental context: the importance of understanding complex gene expression patterns in evolution.

    PubMed

    Signor, Sarah A; Arbeitman, Michelle N; Nuzhdin, Sergey V

    2016-05-01

    Animal development is the product of distinct components and interactions-genes, regulatory networks, and cells-and it exhibits emergent properties that cannot be inferred from the components in isolation. Often the focus is on the genotype-to-phenotype map, overlooking the process of development that turns one into the other. We propose a move toward micro-evolutionary analysis of development, incorporating new tools that enable cell type resolution and single-cell microscopy. Using the sex determination pathway in Drosophila to illustrate potential avenues of research, we highlight some of the questions that these emerging technologies can address. For example, they provide an unprecedented opportunity to study heterogeneity within cell populations, and the potential to add the dimension of time to gene regulatory network analysis. Challenges still remain in developing methods to analyze this data and to increase the throughput. However this line of research has the potential to bridge the gaps between previously more disparate fields, such as population genetics and development, opening up new avenues of research. © 2016 Wiley Periodicals, Inc.

  5. Demystifying the cytokine network: Mathematical models point the way.

    PubMed

    Morel, Penelope A; Lee, Robin E C; Faeder, James R

    2017-10-01

    Cytokines provide the means by which immune cells communicate with each other and with parenchymal cells. There are over one hundred cytokines and many exist in families that share receptor components and signal transduction pathways, creating complex networks. Reductionist approaches to understanding the role of specific cytokines, through the use of gene-targeted mice, have revealed further complexity in the form of redundancy and pleiotropy in cytokine function. Creating an understanding of the complex interactions between cytokines and their target cells is challenging experimentally. Mathematical and computational modeling provides a robust set of tools by which complex interactions between cytokines can be studied and analyzed, in the process creating novel insights that can be further tested experimentally. This review will discuss and provide examples of the different modeling approaches that have been used to increase our understanding of cytokine networks. This includes discussion of knowledge-based and data-driven modeling approaches and the recent advance in single-cell analysis. The use of modeling to optimize cytokine-based therapies will also be discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. A platform for rapid prototyping of synthetic gene networks in mammalian cells

    PubMed Central

    Duportet, Xavier; Wroblewska, Liliana; Guye, Patrick; Li, Yinqing; Eyquem, Justin; Rieders, Julianne; Rimchala, Tharathorn; Batt, Gregory; Weiss, Ron

    2014-01-01

    Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to genetically program cells is currently hampered by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks. To address this problem, here we present a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. We demonstrate the potential of this framework by assembling and integrating different functional mammalian regulatory networks including the largest gene circuit built and chromosomally integrated to date (6 transcription units, 27kb) encoding an inducible memory device. Using a library of 18 different circuits as a proof of concept, we also demonstrate that our method enables one-pot/single-flask chromosomal integration and screening of circuit libraries. This rapid and powerful prototyping platform is well suited for comparative studies of genetic regulatory elements, genes and multi-gene circuits as well as facile development of libraries of isogenic engineered cell lines. PMID:25378321

  7. Cytokines and cytokine networks target neurons to modulate long-term potentiation.

    PubMed

    Prieto, G Aleph; Cotman, Carl W

    2017-04-01

    Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Cytokines and cytokine networks target neurons to modulate long-term potentiation

    PubMed Central

    Prieto, G. Aleph; Cotman, Carl W.

    2017-01-01

    Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines. PMID:28377062

  9. BTG interacts with retinoblastoma to control cell fate in Dictyostelium.

    PubMed

    Conte, Daniele; MacWilliams, Harry K; Ceccarelli, Adriano

    2010-03-12

    In the genesis of many tissues, a phase of cell proliferation is followed by cell cycle exit and terminal differentiation. The latter two processes overlap: genes involved in the cessation of growth may also be important in triggering differentiation. Though conceptually distinct, they are often causally related and functional interactions between the cell cycle machinery and cell fate control networks are fundamental to coordinate growth and differentiation. A switch from proliferation to differentiation may also be important in the life cycle of single-celled organisms, and genes which arose as regulators of microbial differentiation may be conserved in higher organisms. Studies in microorganisms may thus contribute to understanding the molecular links between cell cycle machinery and the determination of cell fate choice networks. Here we show that in the amoebozoan D. discoideum, an ortholog of the metazoan antiproliferative gene btg controls cell fate, and that this function is dependent on the presence of a second tumor suppressor ortholog, the retinoblastoma-like gene product. Specifically, we find that btg-overexpressing cells preferentially adopt a stalk cell (and, more particularly, an Anterior-Like Cell) fate. No btg-dependent preference for ALC fate is observed in cells in which the retinoblastoma-like gene has been genetically inactivated. Dictyostelium btg is the only example of non-metazoan member of the BTG family characterized so far, suggesting that a genetic interaction between btg and Rb predated the divergence between dictyostelids and metazoa. While the requirement for retinoblastoma function for BTG antiproliferative activity in metazoans is known, an interaction of these genes in the control of cell fate has not been previously documented. Involvement of a single pathway in the control of mutually exclusive processes may have relevant implication in the evolution of multicellularity.

  10. Control of cancer-related signal transduction networks

    NASA Astrophysics Data System (ADS)

    Albert, Reka

    2013-03-01

    Intra-cellular signaling networks are crucial to the maintenance of cellular homeostasis and for cell behavior (growth, survival, apoptosis, movement). Mutations or alterations in the expression of elements of cellular signaling networks can lead to incorrect behavioral decisions that could result in tumor development and/or the promotion of cell migration and metastasis. Thus, mitigation of the cascading effects of such dysregulations is an important control objective. My group at Penn State is collaborating with wet-bench biologists to develop and validate predictive models of various biological systems. Over the years we found that discrete dynamic modeling is very useful in molding qualitative interaction information into a predictive model. We recently demonstrated the effectiveness of network-based targeted manipulations on mitigating the disease T cell large granular lymphocyte (T-LGL) leukemia. The root of this disease is the abnormal survival of T cells which, after successfully fighting an infection, should undergo programmed cell death. We synthesized the relevant network of within-T-cell interactions from the literature, integrated it with qualitative knowledge of the dysregulated (abnormal) states of several network components, and formulated a Boolean dynamic model. The model indicated that the system possesses a steady state corresponding to the normal cell death state and a T-LGL steady state corresponding to the abnormal survival state. For each node, we evaluated the restorative manipulation consisting of maintaining the node in the state that is the opposite of its T-LGL state, e.g. knocking it out if it is overexpressed in the T-LGL state. We found that such control of any of 15 nodes led to the disappearance of the T-LGL steady state, leaving cell death as the only potential outcome from any initial condition. In four additional cases the probability of reaching the T-LGL state decreased dramatically, thus these nodes are also possible control targets. Our collaborators validated two of these predicted control mechanisms experimentally. Our work suggests that external control of a single node can be a fruitful therapeutic strategy.

  11. Modeling heterogeneous responsiveness of intrinsic apoptosis pathway

    PubMed Central

    2013-01-01

    Background Apoptosis is a cell suicide mechanism that enables multicellular organisms to maintain homeostasis and to eliminate individual cells that threaten the organism’s survival. Dependent on the type of stimulus, apoptosis can be propagated by extrinsic pathway or intrinsic pathway. The comprehensive understanding of the molecular mechanism of apoptotic signaling allows for development of mathematical models, aiming to elucidate dynamical and systems properties of apoptotic signaling networks. There have been extensive efforts in modeling deterministic apoptosis network accounting for average behavior of a population of cells. Cellular networks, however, are inherently stochastic and significant cell-to-cell variability in apoptosis response has been observed at single cell level. Results To address the inevitable randomness in the intrinsic apoptosis mechanism, we develop a theoretical and computational modeling framework of intrinsic apoptosis pathway at single-cell level, accounting for both deterministic and stochastic behavior. Our deterministic model, adapted from the well-accepted Fussenegger model, shows that an additional positive feedback between the executioner caspase and the initiator caspase plays a fundamental role in yielding the desired property of bistability. We then examine the impact of intrinsic fluctuations of biochemical reactions, viewed as intrinsic noise, and natural variation of protein concentrations, viewed as extrinsic noise, on behavior of the intrinsic apoptosis network. Histograms of the steady-state output at varying input levels show that the intrinsic noise could elicit a wider region of bistability over that of the deterministic model. However, the system stochasticity due to intrinsic fluctuations, such as the noise of steady-state response and the randomness of response delay, shows that the intrinsic noise in general is insufficient to produce significant cell-to-cell variations at physiologically relevant level of molecular numbers. Furthermore, the extrinsic noise represented by random variations of two key apoptotic proteins, namely Cytochrome C and inhibitor of apoptosis proteins (IAP), is modeled separately or in combination with intrinsic noise. The resultant stochasticity in the timing of intrinsic apoptosis response shows that the fluctuating protein variations can induce cell-to-cell stochastic variability at a quantitative level agreeing with experiments. Finally, simulations illustrate that the mean abundance of fluctuating IAP protein is positively correlated with the degree of cellular stochasticity of the intrinsic apoptosis pathway. Conclusions Our theoretical and computational study shows that the pronounced non-genetic heterogeneity in intrinsic apoptosis responses among individual cells plausibly arises from extrinsic rather than intrinsic origin of fluctuations. In addition, it predicts that the IAP protein could serve as a potential therapeutic target for suppression of the cell-to-cell variation in the intrinsic apoptosis responsiveness. PMID:23875784

  12. Traffic sharing algorithms for hybrid mobile networks

    NASA Technical Reports Server (NTRS)

    Arcand, S.; Murthy, K. M. S.; Hafez, R.

    1995-01-01

    In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

  13. The Membrane Skeleton Controls Diffusion Dynamics and Signaling through the B Cell Receptor

    PubMed Central

    Treanor, Bebhinn; Depoil, David; Gonzalez-Granja, Aitor; Barral, Patricia; Weber, Michele; Dushek, Omer; Bruckbauer, Andreas; Batista, Facundo D.

    2010-01-01

    Summary Early events of B cell activation after B cell receptor (BCR) triggering have been well characterized. However, little is known about the steady state of the BCR on the cell surface. Here, we simultaneously visualize single BCR particles and components of the membrane skeleton. We show that an ezrin- and actin-defined network influenced steady-state BCR diffusion by creating boundaries that restrict BCR diffusion. We identified the intracellular domain of Igβ as important in mediating this restriction in diffusion. Importantly, alteration of this network was sufficient to induce robust intracellular signaling and concomitant increase in BCR mobility. Moreover, by using B cells deficient in key signaling molecules, we show that this signaling was most probably initiated by the BCR. Thus, our results suggest the membrane skeleton plays a crucial function in controlling BCR dynamics and thereby signaling, in a way that could be important for understanding tonic signaling necessary for B cell development and survival. PMID:20171124

  14. Cell-Type-Specific Transcriptome Analysis in the Drosophila Mushroom Body Reveals Memory-Related Changes in Gene Expression.

    PubMed

    Crocker, Amanda; Guan, Xiao-Juan; Murphy, Coleen T; Murthy, Mala

    2016-05-17

    Learning and memory formation in Drosophila rely on a network of neurons in the mushroom bodies (MBs). Whereas numerous studies have delineated roles for individual cell types within this network in aspects of learning or memory, whether or not these cells can also be distinguished by the genes they express remains unresolved. In addition, the changes in gene expression that accompany long-term memory formation within the MBs have not yet been studied by neuron type. Here, we address both issues by performing RNA sequencing on single cell types (harvested via patch pipets) within the MB. We discover that the expression of genes that encode cell surface receptors is sufficient to identify cell types and that a subset of these genes, required for sensory transduction in peripheral sensory neurons, is not only expressed within individual neurons of the MB in the central brain, but is also critical for memory formation. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  15. Extracellular calcium controls the expression of two different forms of ripple-like hippocampal oscillations.

    PubMed

    Aivar, Paloma; Valero, Manuel; Bellistri, Elisa; Menendez de la Prida, Liset

    2014-02-19

    Hippocampal high-frequency oscillations (HFOs) are prominent in physiological and pathological conditions. During physiological ripples (100-200 Hz), few pyramidal cells fire together coordinated by rhythmic inhibitory potentials. In the epileptic hippocampus, fast ripples (>200 Hz) reflect population spikes (PSs) from clusters of bursting cells, but HFOs in the ripple and the fast ripple range are vastly intermixed. What is the meaning of this frequency range? What determines the expression of different HFOs? Here, we used different concentrations of Ca(2+) in a physiological range (1-3 mM) to record local field potentials and single cells in hippocampal slices from normal rats. Surprisingly, we found that this sole manipulation results in the emergence of two forms of HFOs reminiscent of ripples and fast ripples recorded in vivo from normal and epileptic rats, respectively. We scrutinized the cellular correlates and mechanisms underlying the emergence of these two forms of HFOs by combining multisite, single-cell and paired-cell recordings in slices prepared from a rat reporter line that facilitates identification of GABAergic cells. We found a major effect of extracellular Ca(2+) in modulating intrinsic excitability and disynaptic inhibition, two critical factors shaping network dynamics. Moreover, locally modulating the extracellular Ca(2+) concentration in an in vivo environment had a similar effect on disynaptic inhibition, pyramidal cell excitability, and ripple dynamics. Therefore, the HFO frequency band reflects a range of firing dynamics of hippocampal networks.

  16. Process-based network decomposition reveals backbone motif structure

    PubMed Central

    Wang, Guanyu; Du, Chenghang; Chen, Hao; Simha, Rahul; Rong, Yongwu; Xiao, Yi; Zeng, Chen

    2010-01-01

    A central challenge in systems biology today is to understand the network of interactions among biomolecules and, especially, the organizing principles underlying such networks. Recent analysis of known networks has identified small motifs that occur ubiquitously, suggesting that larger networks might be constructed in the manner of electronic circuits by assembling groups of these smaller modules. Using a unique process-based approach to analyzing such networks, we show for two cell-cycle networks that each of these networks contains a giant backbone motif spanning all the network nodes that provides the main functional response. The backbone is in fact the smallest network capable of providing the desired functionality. Furthermore, the remaining edges in the network form smaller motifs whose role is to confer stability properties rather than provide function. The process-based approach used in the above analysis has additional benefits: It is scalable, analytic (resulting in a single analyzable expression that describes the behavior), and computationally efficient (all possible minimal networks for a biological process can be identified and enumerated). PMID:20498084

  17. Preface of the "Symposium on Mathematical Models and Methods to investigate Heterogeneity in Cell and Cell Population Biology"

    NASA Astrophysics Data System (ADS)

    Clairambault, Jean

    2016-06-01

    This session investigates hot topics related to mathematical representations of cell and cell population dynamics in biology and medicine, in particular, but not only, with applications to cancer. Methods in mathematical modelling and analysis, and in statistical inference using single-cell and cell population data, should contribute to focus this session on heterogeneity in cell populations. Among other methods are proposed: a) Intracellular protein dynamics and gene regulatory networks using ordinary/partial/delay differential equations (ODEs, PDEs, DDEs); b) Representation of cell population dynamics using agent-based models (ABMs) and/or PDEs; c) Hybrid models and multiscale models to integrate single-cell dynamics into cell population behaviour; d) Structured cell population dynamics and asymptotic evolution w.r.t. relevant traits; e) Heterogeneity in cancer cell populations: origin, evolution, phylogeny and methods of reconstruction; f) Drug resistance as an evolutionary phenotype: predicting and overcoming it in therapeutics; g) Theoretical therapeutic optimisation of combined drug treatments in cancer cell populations and in populations of other organisms, such as bacteria.

  18. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

    PubMed Central

    2017-01-01

    Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalized. In particular, sequencing errors in the UMI sequence are often ignored or else resolved in an ad hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single-cell RNA-seq data sets. Reproducibility between iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package. PMID:28100584

  19. RNA regulatory networks diversified through curvature of the PUF protein scaffold

    DOE PAGES

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P.; ...

    2015-09-14

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p–RNA complexes reveal that the protein scaffold presents an exceptionally flat and extendedmore » interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks.« less

  20. RNA regulatory networks diversified through curvature of the PUF protein scaffold

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

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P.

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p–RNA complexes reveal that the protein scaffold presents an exceptionally flat and extendedmore » interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks.« less

  1. Network Medicine: A Network-based Approach to Human Disease

    PubMed Central

    Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph

    2011-01-01

    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525

  2. Pinched-flow hydrodynamic stretching of single-cells.

    PubMed

    Dudani, Jaideep S; Gossett, Daniel R; Tse, Henry T K; Di Carlo, Dino

    2013-09-21

    Reorganization of cytoskeletal networks, condensation and decondensation of chromatin, and other whole cell structural changes often accompany changes in cell state and can reflect underlying disease processes. As such, the observable mechanical properties, or mechanophenotype, which is closely linked to intracellular architecture, can be a useful label-free biomarker of disease. In order to make use of this biomarker, a tool to measure cell mechanical properties should accurately characterize clinical specimens that consist of heterogeneous cell populations or contain small diseased subpopulations. Because of the heterogeneity and potential for rare populations in clinical samples, single-cell, high-throughput assays are ideally suited. Hydrodynamic stretching has recently emerged as a powerful method for carrying out mechanical phenotyping. Importantly, this method operates independently of molecular probes, reducing cost and sample preparation time, and yields information-rich signatures of cell populations through significant image analysis automation, promoting more widespread adoption. In this work, we present an alternative mode of hydrodynamic stretching where inertially-focused cells are squeezed in flow by perpendicular high-speed pinch flows that are extracted from the single inputted cell suspension. The pinched-flow stretching method reveals expected differences in cell deformability in two model systems. Furthermore, hydraulic circuit design is used to tune stretching forces and carry out multiple stretching modes (pinched-flow and extensional) in the same microfluidic channel with a single fluid input. The ability to create a self-sheathing flow from a single input solution should have general utility for other cytometry systems and the pinched-flow design enables an order of magnitude higher throughput (65,000 cells s(-1)) compared to our previously reported deformability cytometry method, which will be especially useful for identification of rare cell populations in clinical body fluids in the future.

  3. Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq.

    PubMed

    Chen, Jun; Suo, Shengbao; Tam, Patrick Pl; Han, Jing-Dong J; Peng, Guangdun; Jing, Naihe

    2017-03-01

    Conventional gene expression studies analyze multiple cells simultaneously or single cells, for which the exact in vivo or in situ position is unknown. Although cellular heterogeneity can be discerned when analyzing single cells, any spatially defined attributes that underpin the heterogeneous nature of the cells cannot be identified. Here, we describe how to use Geo-seq, a method that combines laser capture microdissection (LCM) and single-cell RNA-seq technology. The combination of these two methods enables the elucidation of cellular heterogeneity and spatial variance simultaneously. The Geo-seq protocol allows the profiling of transcriptome information from only a small number cells and retains their native spatial information. This protocol has wide potential applications to address biological and pathological questions of cellular properties such as prospective cell fates, biological function and the gene regulatory network. Geo-seq has been applied to investigate the spatial transcriptome of mouse early embryo, mouse brain, and pathological liver and sperm tissues. The entire protocol from tissue collection and microdissection to sequencing requires ∼5 d, Data analysis takes another 1 or 2 weeks, depending on the amount of data and the speed of the processor.

  4. Efficient Steplike Carrier Multiplication in Percolative Networks of Epitaxially Connected PbSe Nanocrystals.

    PubMed

    Kulkarni, Aditya; Evers, Wiel H; Tomić, Stanko; Beard, Matthew C; Vanmaekelbergh, Daniel; Siebbeles, Laurens D A

    2018-01-23

    Carrier multiplication (CM) is a process in which a single photon excites two or more electrons. CM is of interest to enhance the efficiency of a solar cell. Until now, CM in thin films and solar cells of semiconductor nanocrystals (NCs) has been found at photon energies well above the minimum required energy of twice the band gap. The high threshold of CM strongly limits the benefits for solar cell applications. We show that CM is more efficient in a percolative network of directly connected PbSe NCs. The CM threshold is at twice the band gap and increases in a steplike fashion with photon energy. A lower CM efficiency is found for a solid of weaker coupled NCs. This demonstrates that the coupling between NCs strongly affects the CM efficiency. According to device simulations, the measured CM efficiency would significantly enhance the power conversion efficiency of a solar cell.

  5. Flow control using audio tones in resonant microfluidic networks: towards cell-phone controlled lab-on-a-chip devices.

    PubMed

    Phillips, Reid H; Jain, Rahil; Browning, Yoni; Shah, Rachana; Kauffman, Peter; Dinh, Doan; Lutz, Barry R

    2016-08-16

    Fluid control remains a challenge in development of portable lab-on-a-chip devices. Here, we show that microfluidic networks driven by single-frequency audio tones create resonant oscillating flow that is predicted by equivalent electrical circuit models. We fabricated microfluidic devices with fluidic resistors (R), inductors (L), and capacitors (C) to create RLC networks with band-pass resonance in the audible frequency range available on portable audio devices. Microfluidic devices were fabricated from laser-cut adhesive plastic, and a "buzzer" was glued to a diaphragm (capacitor) to integrate the actuator on the device. The AC flowrate magnitude was measured by imaging oscillation of bead tracers to allow direct comparison to the RLC circuit model across the frequency range. We present a systematic build-up from single-channel systems to multi-channel (3-channel) networks, and show that RLC circuit models predict complex frequency-dependent interactions within multi-channel networks. Finally, we show that adding flow rectifying valves to the network creates pumps that can be driven by amplified and non-amplified audio tones from common audio devices (iPod and iPhone). This work shows that RLC circuit models predict resonant flow responses in multi-channel fluidic networks as a step towards microfluidic devices controlled by audio tones.

  6. Cracking the egg: virtual embryogenesis of real robots.

    PubMed

    Cussat-Blanc, Sylvain; Pollack, Jordan

    2014-01-01

    All multicellular living beings are created from a single cell. A developmental process, called embryogenesis, takes this first fertilized cell down a complex path of reproduction, migration, and specialization into a complex organism adapted to its environment. In most cases, the first steps of the embryogenesis take place in a protected environment such as in an egg or in utero. Starting from this observation, we propose a new approach to the generation of real robots, strongly inspired by living systems. Our robots are composed of tens of specialized cells, grown from a single cell using a bio-inspired virtual developmental process. Virtual cells, controlled by gene regulatory networks, divide, migrate, and specialize to produce the robot's body plan (morphology), and then the robot is manually built from this plan. Because the robot is as easy to assemble as Lego, the building process could be easily automated.

  7. Cooperative Adaptive Responses in Gene Regulatory Networks with Many Degrees of Freedom

    PubMed Central

    Inoue, Masayo; Kaneko, Kunihiko

    2013-01-01

    Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components. PMID:23592959

  8. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    PubMed Central

    Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

  9. Accurate Encoding and Decoding by Single Cells: Amplitude Versus Frequency Modulation

    PubMed Central

    Micali, Gabriele; Aquino, Gerardo; Richards, David M.; Endres, Robert G.

    2015-01-01

    Cells sense external concentrations and, via biochemical signaling, respond by regulating the expression of target proteins. Both in signaling networks and gene regulation there are two main mechanisms by which the concentration can be encoded internally: amplitude modulation (AM), where the absolute concentration of an internal signaling molecule encodes the stimulus, and frequency modulation (FM), where the period between successive bursts represents the stimulus. Although both mechanisms have been observed in biological systems, the question of when it is beneficial for cells to use either AM or FM is largely unanswered. Here, we first consider a simple model for a single receptor (or ion channel), which can either signal continuously whenever a ligand is bound, or produce a burst in signaling molecule upon receptor binding. We find that bursty signaling is more accurate than continuous signaling only for sufficiently fast dynamics. This suggests that modulation based on bursts may be more common in signaling networks than in gene regulation. We then extend our model to multiple receptors, where continuous and bursty signaling are equivalent to AM and FM respectively, finding that AM is always more accurate. This implies that the reason some cells use FM is related to factors other than accuracy, such as the ability to coordinate expression of multiple genes or to implement threshold crossing mechanisms. PMID:26030820

  10. A conversation across generations: soma-germ cell crosstalk in plants.

    PubMed

    Feng, Xiaoqi; Zilberman, Daniel; Dickinson, Hugh

    2013-02-11

    Plants undergo alternation of generation in which reproductive cells develop in the plant body ("sporophytic generation") and then differentiate into a multicellular gamete-forming "gametophytic generation." Different populations of helper cells assist in this transgenerational journey, with somatic tissues supporting early development and single nurse cells supporting gametogenesis. New data reveal a two-way relationship between early reproductive cells and their helpers involving complex epigenetic and signaling networks determining cell number and fate. Later, the egg cell plays a central role in specifying accessory cells, whereas in both gametophytes, companion cells contribute non-cell-autonomously to the epigenetic landscape of the gamete genomes. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Synthetic networks in microbial communities

    NASA Astrophysics Data System (ADS)

    Suel, Gurol

    2015-03-01

    While bacteria are single celled organisms, they predominantly reside in structured communities known as biofilms. Cells in biofilms are encapsulated and protected by the extracellular matrix (ECM), which also confines cells in space. During biofilm development, microbial cells are organized in space and over time. Little is known regarding the processes that drive the spatio-temporal organization of microbial communities. Here I will present our latest efforts that utilize synthetic biology approaches to uncover the organizational principles that drive biofilm development. I will also discuss the possible implications of our recent findings in terms of the cost and benefit to biofilm cells.

  12. Immunomediated Pan-cancer Regulation Networks are Dominant Fingerprints After Treatment of Cell Lines with Demethylation.

    PubMed

    El Baroudi, Mariama; Cinti, Caterina; Capobianco, Enrico

    2016-01-01

    Pan-cancer studies are particularly relevant not only for addressing the complexity of the inherently observed heterogeneity but also for identifying clinically relevant features that may be common to the cancer types. Immune system regulations usually reveal synergistic modulation with other cancer mechanisms and in combination provide insights on possible advances in cancer immunotherapies. Network inference is a powerful approach to decipher pan-cancer systems dynamics. The methodology proposed in this study elucidates the impacts of epigenetic treatment on the drivers of complex pan-cancer regulation circuits involving cell lines of five cancer types. These patterns were observed from differential gene expression measurements following demethylation with 5-azacytidine. Networks were built to establish associations of phenotypes at molecular level with cancer hallmarks through both transcriptional and post-transcriptional regulation mechanisms. The most prominent feature that emerges from our integrative network maps, linking pathway landscapes to disease and drug-target associations, refers primarily to a mosaic of immune-system crosslinked influences. Therefore, characteristics initially evidenced in single cancer maps become motifs well summarized by network cores and fingerprints.

  13. Multistability in the lactose utilization network of Escherichia coli

    NASA Astrophysics Data System (ADS)

    Ozbudak, Ertugrul M.; Thattai, Mukund; Lim, Han N.; Shraiman, Boris I.; van Oudenaarden, Alexander

    2004-02-01

    Multistability, the capacity to achieve multiple internal states in response to a single set of external inputs, is the defining characteristic of a switch. Biological switches are essential for the determination of cell fate in multicellular organisms, the regulation of cell-cycle oscillations during mitosis and the maintenance of epigenetic traits in microbes. The multistability of several natural and synthetic systems has been attributed to positive feedback loops in their regulatory networks. However, feedback alone does not guarantee multistability. The phase diagram of a multistable system, a concise description of internal states as key parameters are varied, reveals the conditions required to produce a functional switch. Here we present the phase diagram of the bistable lactose utilization network of Escherichia coli. We use this phase diagram, coupled with a mathematical model of the network, to quantitatively investigate processes such as sugar uptake and transcriptional regulation in vivo. We then show how the hysteretic response of the wild-type system can be converted to an ultrasensitive graded response. The phase diagram thus serves as a sensitive probe of molecular interactions and as a powerful tool for rational network design.

  14. Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro

    PubMed Central

    Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P. C.; Livesey, Frederick J.

    2015-01-01

    A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. PMID:26395144

  15. Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

    PubMed

    Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

    2015-09-15

    A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

  16. Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

    PubMed Central

    2014-01-01

    Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313

  17. Dynamic generation of concentration- and temporal-dependent chemical signals in an integrated microfluidic device for single-cell analysis.

    PubMed

    Gonzalez-Suarez, Alan Mauricio; Peña-Del Castillo, Johanna G; Hernandez-Cruz, Arturo; Garcia-Cordero, Jose Luis

    2018-06-19

    Intracellular signaling pathways are affected by the temporal nature of external chemical signaling molecules such as neuro-transmitters or hormones. Developing high-throughput technologies to mimic these time-varying chemical signals and to analyze the response of single cells would deepen our understanding of signaling networks. In this work, we introduce a microfluidic platform to stimulate hundreds of single cells with chemical waveforms of tunable frequency and amplitude. Our device produces a linear gradient of 9 concentrations that are delivered to an equal number of chambers, each containing 492 microwells, where individual cells are captured. The device can alternate between the different stimuli concentrations and a control buffer, with a maximum operating frequency of 33 mHz that can be adjusted from a computer. Fluorescent time-lapse microscopy enables to obtain hundreds of thousands of data points from one experiment. We characterized the gradient performance and stability by staining hundreds of cells with calcein AM. We also assessed the capacity of our device to introduce periodic chemical stimuli of different amplitudes and frequencies. To demonstrate our device performance, we studied the dynamics of intracellular Ca2+ release from intracellular stores of HEK cells when stimulated with carbachol at 4.5 and 20 mHz. Our work opens the possibility of characterizing the dynamic responses in real time of signaling molecules to time-varying chemical stimuli with single cell resolution.

  18. Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.

    PubMed

    Pena, Rodrigo F O; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C; Lindner, Benjamin

    2018-01-01

    Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as indicated by comparison with simulation results of large recurrent networks. Our method can help to elucidate how network heterogeneity shapes the asynchronous state in recurrent neural networks.

  19. An NV-Diamond Magnetic Imager for Neuroscience

    NASA Astrophysics Data System (ADS)

    Turner, Matthew; Schloss, Jennifer; Bauch, Erik; Hart, Connor; Walsworth, Ronald

    2017-04-01

    We present recent progress towards imaging time-varying magnetic fields from neurons using nitrogen-vacancy centers in diamond. The diamond neuron imager is noninvasive, label-free, and achieves single-cell resolution and state-of-the-art broadband sensitivity. By imaging magnetic fields from injected currents in mammalian neurons, we will map functional neuronal network connections and illuminate biophysical properties of neurons invisible to traditional electrophysiology. Furthermore, through enhancing magnetometer sensitivity, we aim to demonstrate real-time imaging of action potentials from networks of mammalian neurons.

  20. Efficient spiking neural network model of pattern motion selectivity in visual cortex.

    PubMed

    Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

    2014-07-01

    Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

  1. The Influence of Neuronal Density and Maturation on Network Activity of Hippocampal Cell Cultures: A Methodological Study

    PubMed Central

    Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

    2013-01-01

    It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm2 cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm2 cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm2 are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs. PMID:24386305

  2. The influence of neuronal density and maturation on network activity of hippocampal cell cultures: a methodological study.

    PubMed

    Biffi, Emilia; Regalia, Giulia; Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

    2013-01-01

    It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm(2) cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm(2) cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm(2) are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs.

  3. Network properties of interstitial cells of Cajal affect intestinal pacemaker activity and motor patterns, according to a mathematical model of weakly coupled oscillators.

    PubMed

    Wei, Ruihan; Parsons, Sean P; Huizinga, Jan D

    2017-03-01

    What is the central question of this study? What are the effects of interstitial cells of Cajal (ICC) network perturbations on intestinal pacemaker activity and motor patterns? What is the main finding and its importance? Two-dimensional modelling of the ICC pacemaker activity according to a phase model of weakly coupled oscillators showed that network properties (coupling strength between oscillators, frequency gradient and frequency noise) strongly influence pacemaker network activity and subsequent motor patterns. The model explains motor patterns observed in physiological conditions and provides predictions and testable hypotheses for effects of ICC loss and frequency modulation on the motor patterns. Interstitial cells of Cajal (ICC) are the pacemaker cells of gut motility and are associated with motility disorders. Interstitial cells of Cajal form a network, but the contributions of its network properties to gut physiology and dysfunction are poorly understood. We modelled an ICC network as a two-dimensional network of weakly coupled oscillators with a frequency gradient and showed changes over time in video and graphical formats. Model parameters were obtained from slow-wave-driven contraction patterns in the mouse intestine and pacemaker slow-wave activities from the cat intestine. Marked changes in propagating oscillation patterns (including changes from propagation to non-propagating) were observed by changing network parameters (coupling strength between oscillators, the frequency gradient and frequency noise), which affected synchronization, propagation velocity and occurrence of dislocations (termination of an oscillation). Complete uncoupling of a circumferential ring of oscillators caused the proximal and distal section to desynchronize, but complete synchronization was maintained with only a single oscillator connecting the sections with high enough coupling. The network of oscillators could withstand loss; even with 40% of oscillators lost randomly within the network, significant synchronization and anterograde propagation remained. A local increase in pacemaker frequency diminished anterograde propagation; the effects were strongly dependent on location, frequency gradient and coupling strength. In summary, the model puts forth the hypothesis that fundamental changes in oscillation patterns (ICC slow-wave activity or circular muscle contractions) can occur through physiological modulation of network properties. Strong evidence is provided to accept the ICC network as a system of coupled oscillators. © 2016 The Authors. Experimental Physiology © 2016 The Physiological Society.

  4. Super-Joule heating in graphene and silver nanowire network

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

    Maize, Kerry; Das, Suprem R.; Sadeque, Sajia

    Transistors, sensors, and transparent conductors based on randomly assembled nanowire networks rely on multi-component percolation for unique and distinctive applications in flexible electronics, biochemical sensing, and solar cells. While conduction models for 1-D and 1-D/2-D networks have been developed, typically assuming linear electronic transport and self-heating, the model has not been validated by direct high-resolution characterization of coupled electronic pathways and thermal response. In this letter, we show the occurrence of nonlinear “super-Joule” self-heating at the transport bottlenecks in networks of silver nanowires and silver nanowire/single layer graphene hybrid using high resolution thermoreflectance (TR) imaging. TR images at the microscopicmore » self-heating hotspots within nanowire network and nanowire/graphene hybrid network devices with submicron spatial resolution are used to infer electrical current pathways. The results encourage a fundamental reevaluation of transport models for network-based percolating conductors.« less

  5. A new link between the retrograde actin flow and focal adhesions.

    PubMed

    Yamashiro, Sawako; Watanabe, Naoki

    2014-11-01

    The retrograde actin flow, continuous centripetal movement of the cell peripheral actin networks, is widely observed in adherent cells. The retrograde flow is believed to facilitate cell migration when linked to cell adhesion molecules. In this review, we summarize our current knowledge regarding the functional relationship between the retrograde actin flow and focal adhesions (FAs). We also introduce our recent study in which single-molecule speckle (SiMS) microscopy dissected the complex interactions between FAs and the local actin flow. FAs do not simply impede the actin flow, but actively attract and remodel the local actin network. Our findings provide a new insight into the mechanisms for protrusion and traction force generation at the cell leading edge. Furthermore, we discuss possible roles of the actin flow-FA interaction based on the accumulated knowledge and our SiMS study. © The Authors 2014. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

  6. From in silico astrocyte cell models to neuron-astrocyte network models: A review.

    PubMed

    Oschmann, Franziska; Berry, Hugues; Obermayer, Klaus; Lenk, Kerstin

    2018-01-01

    The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Nonequilibrium stabilization of an RNA/protein droplet emulsion by nuclear actin

    NASA Astrophysics Data System (ADS)

    Brangwynne, Clifford

    2013-03-01

    Actin plays a structural role in the cytoplasm. However, actin takes on new functions and structures in the nucleus that are poorly understood. The nuclei of the large oocytes of the frog X. laevisspecifically accumulate actin to reach high concentrations; however, it remains unclear if this actin polymerizes into a network, and what, if any, structural role such an actin network might play. Here, we use microrheological and confocal imaging techniques to probe the local architecture and mechanics of the nucleus. Our data show that actin forms a weak network that spatially organizes the nucleus by kinetically stabilizing embedded liquid-like RNA/protein bodies which are important for cell growth. In actin-disrupted nuclei this RNA/protein droplet emulsion is destabilized leading to homotypic coalescence into single large droplets. Our data provide intriguing new insights into why large cell nuclei require an actin-based structural scaffold.

  8. Bayesian Networks Predict Neuronal Transdifferentiation.

    PubMed

    Ainsworth, Richard I; Ai, Rizi; Ding, Bo; Li, Nan; Zhang, Kai; Wang, Wei

    2018-05-30

    We employ the language of Bayesian networks to systematically construct gene-regulation topologies from deep-sequencing single-nucleus RNA-Seq data for human neurons. From the perspective of the cell-state potential landscape, we identify attractors that correspond closely to different neuron subtypes. Attractors are also recovered for cell states from an independent data set confirming our models accurate description of global genetic regulations across differing cell types of the neocortex (not included in the training data). Our model recovers experimentally confirmed genetic regulations and community analysis reveals genetic associations in common pathways. Via a comprehensive scan of all theoretical three-gene perturbations of gene knockout and overexpression, we discover novel neuronal trans-differrentiation recipes (including perturbations of SATB2, GAD1, POU6F2 and ADARB2) for excitatory projection neuron and inhibitory interneuron subtypes. Copyright © 2018, G3: Genes, Genomes, Genetics.

  9. Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays.

    PubMed

    Gertz, Monica L; Baker, Zachary; Jose, Sharon; Peixoto, Nathalia

    2017-05-29

    Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network dynamics in neuronal cultures. In contrast with more traditional methods, such as patch-clamping, which can only record activity from a single cell, MEAs can record simultaneously from multiple sites in a network, without requiring the arduous task of placing each electrode individually. Moreover, numerous control and stimulation configurations can be easily applied within the same experimental setup, allowing for a broad range of dynamics to be explored. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Mouse neuronal cells cultured on MEAs display an increase in response following training induced by electrical stimulation. This protocol demonstrates how to culture neuronal cells on MEAs; successfully record from over 95% of the plated dishes; establish a protocol to train the networks to respond to patterns of stimulation; and sort, plot, and interpret the results from such experiments. The use of a proprietary system for stimulating and recording neuronal cultures is demonstrated. Software packages are also used to sort neuronal units. A custom-designed graphical user interface is used to visualize post-stimulus time histograms, inter-burst intervals, and burst duration, as well as to compare the cellular response to stimulation before and after a training protocol. Finally, representative results and future directions of this research effort are discussed.

  10. Fibered Confocal Fluorescence Microscopy for the Noninvasive Imaging of Langerhans Cells in Macaques.

    PubMed

    Todorova, Biliana; Salabert, Nina; Tricot, Sabine; Boisgard, Raphaël; Rathaux, Mélanie; Le Grand, Roger; Chapon, Catherine

    2017-01-01

    We developed a new approach to visualize skin Langerhans cells by in vivo fluorescence imaging in nonhuman primates. Macaques were intradermally injected with a monoclonal, fluorescently labeled antibody against HLA-DR molecule and were imaged for up to 5 days by fibered confocal microscopy (FCFM). The network of skin Langerhans cells was visualized by in vivo fibered confocal fluorescence microscopy. Quantification of Langerhans cells revealed no changes to cell density with time. Ex vivo experiments confirmed that injected fluorescent HLA-DR antibody specifically targeted Langerhans cells in the epidermis. This study demonstrates the feasibility of single-cell, in vivo imaging as a noninvasive technique to track Langerhans cells in nontransgenic animals.

  11. Viruses and tetraspanins: lessons from single molecule approaches.

    PubMed

    Dahmane, Selma; Rubinstein, Eric; Milhiet, Pierre-Emmanuel

    2014-05-05

    Tetraspanins are four-span membrane proteins that are widely distributed in multi-cellular organisms and involved in several infectious diseases. They have the unique property to form a network of protein-protein interaction within the plasma membrane, due to the lateral associations with one another and with other membrane proteins. Tracking tetraspanins at the single molecule level using fluorescence microscopy has revealed the membrane behavior of the tetraspanins CD9 and CD81 in epithelial cell lines, providing a first dynamic view of this network. Single molecule tracking highlighted that these 2 proteins can freely diffuse within the plasma membrane but can also be trapped, permanently or transiently, in tetraspanin-enriched areas. More recently, a similar strategy has been used to investigate tetraspanin membrane behavior in the context of human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) infection. In this review we summarize the main results emphasizing the relationship in terms of membrane partitioning between tetraspanins, some of their partners such as Claudin-1 and EWI-2, and viral proteins during infection. These results will be analyzed in the context of other membrane microdomains, stressing the difference between raft and tetraspanin-enriched microdomains, but also in comparison with virus diffusion at the cell surface. New advanced single molecule techniques that could help to further explore tetraspanin assemblies will be also discussed.

  12. Nanostructured cavity devices for extracellular stimulation of HL-1 cells

    NASA Astrophysics Data System (ADS)

    Czeschik, Anna; Rinklin, Philipp; Derra, Ulrike; Ullmann, Sabrina; Holik, Peter; Steltenkamp, Siegfried; Offenhäusser, Andreas; Wolfrum, Bernhard

    2015-05-01

    Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network.Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network. Electronic supplementary information (ESI) available: Comparison of non-filtered and Savitzky-Golay filtered action potential recordings, electrical signals and corresponding optical signals. See DOI: 10.1039/c5nr01690h

  13. Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons.

    PubMed

    Probst, Dimitri; Petrovici, Mihai A; Bytschok, Ilja; Bill, Johannes; Pecevski, Dejan; Schemmel, Johannes; Meier, Karlheinz

    2015-01-01

    The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell level. In this article, we describe a complete theoretical framework for building networks of leaky integrate-and-fire neurons that can sample from arbitrary probability distributions over binary random variables. We test our framework for a model inference task based on a psychophysical phenomenon (the Knill-Kersten optical illusion) and further assess its performance when applied to randomly generated distributions. As the local computations performed by the network strongly depend on the interaction between neurons, we compare several types of couplings mediated by either single synapses or interneuron chains. Due to its robustness to substrate imperfections such as parameter noise and background noise correlations, our model is particularly interesting for implementation on novel, neuro-inspired computing architectures, which can thereby serve as a fast, low-power substrate for solving real-world inference problems.

  14. Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons

    PubMed Central

    Probst, Dimitri; Petrovici, Mihai A.; Bytschok, Ilja; Bill, Johannes; Pecevski, Dejan; Schemmel, Johannes; Meier, Karlheinz

    2015-01-01

    The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell level. In this article, we describe a complete theoretical framework for building networks of leaky integrate-and-fire neurons that can sample from arbitrary probability distributions over binary random variables. We test our framework for a model inference task based on a psychophysical phenomenon (the Knill-Kersten optical illusion) and further assess its performance when applied to randomly generated distributions. As the local computations performed by the network strongly depend on the interaction between neurons, we compare several types of couplings mediated by either single synapses or interneuron chains. Due to its robustness to substrate imperfections such as parameter noise and background noise correlations, our model is particularly interesting for implementation on novel, neuro-inspired computing architectures, which can thereby serve as a fast, low-power substrate for solving real-world inference problems. PMID:25729361

  15. Network Medicine: From Cellular Networks to the Human Diseasome

    NASA Astrophysics Data System (ADS)

    Barabasi, Albert-Laszlo

    2014-03-01

    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

  16. Exploring molecular networks using MONET ontology.

    PubMed

    Silva, João Paulo Müller da; Lemke, Ney; Mombach, José Carlos; Souza, José Guilherme Camargo de; Sinigaglia, Marialva; Vieira, Renata

    2006-03-31

    The description of the complex molecular network responsible for cell behavior requires new tools to integrate large quantities of experimental data in the design of biological information systems. These tools could be used in the characterization of these networks and in the formulation of relevant biological hypotheses. The building of an ontology is a crucial step because it integrates in a coherent framework the concepts necessary to accomplish such a task. We present MONET (molecular network), an extensible ontology and an architecture designed to facilitate the integration of data originating from different public databases in a single- and well-documented relational database, that is compatible with MONET formal definition. We also present an example of an application that can easily be implemented using these tools.

  17. Regulation of a transcription factor network by Cdk1 coordinates late cell cycle gene expression

    PubMed Central

    Landry, Benjamin D; Mapa, Claudine E; Arsenault, Heather E; Poti, Kristin E; Benanti, Jennifer A

    2014-01-01

    To maintain genome stability, regulators of chromosome segregation must be expressed in coordination with mitotic events. Expression of these late cell cycle genes is regulated by cyclin-dependent kinase (Cdk1), which phosphorylates a network of conserved transcription factors (TFs). However, the effects of Cdk1 phosphorylation on many key TFs are not known. We find that elimination of Cdk1-mediated phosphorylation of four S-phase TFs decreases expression of many late cell cycle genes, delays mitotic progression, and reduces fitness in budding yeast. Blocking phosphorylation impairs degradation of all four TFs. Consequently, phosphorylation-deficient mutants of the repressors Yox1 and Yhp1 exhibit increased promoter occupancy and decreased expression of their target genes. Interestingly, although phosphorylation of the transcriptional activator Hcm1 on its N-terminus promotes its degradation, phosphorylation on its C-terminus is required for its activity, indicating that Cdk1 both activates and inhibits a single TF. We conclude that Cdk1 promotes gene expression by both activating transcriptional activators and inactivating transcriptional repressors. Furthermore, our data suggest that coordinated regulation of the TF network by Cdk1 is necessary for faithful cell division. PMID:24714560

  18. Regulation of a transcription factor network by Cdk1 coordinates late cell cycle gene expression.

    PubMed

    Landry, Benjamin D; Mapa, Claudine E; Arsenault, Heather E; Poti, Kristin E; Benanti, Jennifer A

    2014-05-02

    To maintain genome stability, regulators of chromosome segregation must be expressed in coordination with mitotic events. Expression of these late cell cycle genes is regulated by cyclin-dependent kinase (Cdk1), which phosphorylates a network of conserved transcription factors (TFs). However, the effects of Cdk1 phosphorylation on many key TFs are not known. We find that elimination of Cdk1-mediated phosphorylation of four S-phase TFs decreases expression of many late cell cycle genes, delays mitotic progression, and reduces fitness in budding yeast. Blocking phosphorylation impairs degradation of all four TFs. Consequently, phosphorylation-deficient mutants of the repressors Yox1 and Yhp1 exhibit increased promoter occupancy and decreased expression of their target genes. Interestingly, although phosphorylation of the transcriptional activator Hcm1 on its N-terminus promotes its degradation, phosphorylation on its C-terminus is required for its activity, indicating that Cdk1 both activates and inhibits a single TF. We conclude that Cdk1 promotes gene expression by both activating transcriptional activators and inactivating transcriptional repressors. Furthermore, our data suggest that coordinated regulation of the TF network by Cdk1 is necessary for faithful cell division.

  19. Overview of Single-Molecule Speckle (SiMS) Microscopy and Its Electroporation-Based Version with Efficient Labeling and Improved Spatiotemporal Resolution.

    PubMed

    Yamashiro, Sawako; Watanabe, Naoki

    2017-07-06

    Live-cell single-molecule imaging was introduced more than a decade ago, and has provided critical information on remodeling of the actin cytoskeleton, the motion of plasma membrane proteins, and dynamics of molecular motor proteins. Actin remodeling has been the best target for this approach because actin and its associated proteins stop diffusing when assembled, allowing visualization of single-molecules of fluorescently-labeled proteins in a state specific manner. The approach based on this simple principle is called Single-Molecule Speckle (SiMS) microscopy. For instance, spatiotemporal regulation of actin polymerization and lifetime distribution of actin filaments can be monitored directly by tracking actin SiMS. In combination with fluorescently labeled probes of various actin regulators, SiMS microscopy has contributed to clarifying the processes underlying recycling, motion and remodeling of the live-cell actin network. Recently, we introduced an electroporation-based method called eSiMS microscopy, with high efficiency, easiness and improved spatiotemporal precision. In this review, we describe the application of live-cell single-molecule imaging to cellular actin dynamics and discuss the advantages of eSiMS microscopy over previous SiMS microscopy.

  20. Temporally precise single-cell resolution optogenetics

    PubMed Central

    Shemesh, Or A.; Tanese, Dimitrii; Zampini, Valeria; Linghu, Changyang; Piatkevich, Kiryl; Ronzitti, Emiliano; Papagiakoumou, Eirini; Boyden, Edward S.; Emiliani, Valentina

    2017-01-01

    Optogenetic control of individual neurons with high temporal precision, within intact mammalian brain circuitry, would enable powerful explorations of how neural circuits operate. Two-photon computer generated holography enables precise sculpting of light, and could in principle enable simultaneous illumination of many neurons in a network, with the requisite temporal precision to simulate accurate neural codes. We designed a high efficacy soma-targeted opsin, finding that fusing the N-terminal 150 residues of kainate receptor subunit 2 (KA2) to the recently discovered high-photocurrent channelrhodopsin CoChR restricted expression of this opsin primarily to the cell body of mammalian cortical neurons. In combination with two-photon holographic stimulation, we found that this somatic CoChR (soCoChR) enabled photostimulation of individual cells in intact cortical circuits with single cell resolution and <1 millisecond temporal precision, and use soCoChR to perform connectivity mapping on intact cortical circuits. PMID:29184208

  1. Single- and double-ion type cross-linked polysiloxane solid electrolytes for lithium cells

    NASA Astrophysics Data System (ADS)

    Tsutsumi, Hiromori; Yamamoto, Masahiro; Morita, Masayuki; Matsuda, Yoshiharu; Nakamura, Takashi; Asai, Hiroyuki

    Polymeric solid electrolytes, that have poly(dimethylsiloxane) (PMS) backbone and cross-linked network, were applied to a rechargeable lithium battery system. Single- (PMS-Li) and double-ion type (PMS-LiClO 4) electrolytes were prepared from the same prepolymers. Lithium electrode in the both electrolytes showed reversible stripping and deposition of lithium. Intercalation and deintercalation processes of lithium ion between lithium-manganese composite oxide (Li xMnO 2) electrode and the electrolytes were also confirmed by cyclic voltammetry, however, peak current decreased with several cycles in both cases. The model cell, Li/PMS-Li/Li xMnO 2 cell had 1.4 mA h g -1 (per 1 g of active material, current density: 3.77 μA cm -2), and the Li/PMS-LiClO 4/Li xMnO 2 cell had 1.6 mA h g -1 (current density: 75.3 μA cm -2).

  2. Generation of WNK1 knockout cell lines by CRISPR/Cas-mediated genome editing.

    PubMed

    Roy, Ankita; Goodman, Joshua H; Begum, Gulnaz; Donnelly, Bridget F; Pittman, Gabrielle; Weinman, Edward J; Sun, Dandan; Subramanya, Arohan R

    2015-02-15

    Sodium-coupled SLC12 cation chloride cotransporters play important roles in cell volume and chloride homeostasis, epithelial fluid secretion, and renal tubular salt reabsorption. These cotransporters are phosphorylated and activated indirectly by With-No-Lysine (WNK) kinases through their downstream effector kinases, Ste20- and SPS1-related proline alanine-rich kinase (SPAK) and oxidative stress-responsive kinase 1 (OSR1). Multiple WNK kinases can coexist within a single cell type, although their relative contributions to SPAK/OSR1 activation and salt transport remain incompletely understood. Deletion of specific WNKs from cells that natively express a functional WNK-SPAK/OSR1 network will help resolve these knowledge gaps. Here, we outline a simple method to selectively knock out full-length WNK1 expression from mammalian cells using RNA-guided clustered regularly interspaced short palindromic repeats/Cas9 endonucleases. Two clonal cell lines were generated by using a single-guide RNA (sgRNA) targeting exon 1 of the WNK1 gene, which produced indels that abolished WNK1 protein expression. Both cell lines exhibited reduced endogenous WNK4 protein abundance, indicating that WNK1 is required for WNK4 stability. Consistent with an on-target effect, the reduced WNK4 abundance was associated with increased expression of the KLHL3/cullin-3 E3 ubiquitin ligase complex and was rescued by exogenous WNK1 overexpression. Although the morphology of the knockout cells was indistinguishable from control, they exhibited low baseline SPAK/OSR1 activity and failed to trigger regulatory volume increase after hypertonic stress, confirming an essential role for WNK1 in cell volume regulation. Collectively, our data show how this new, powerful, and accessible gene-editing technology can be used to dissect and analyze WNK signaling networks.

  3. A multi-scale convolutional neural network for phenotyping high-content cellular images.

    PubMed

    Godinez, William J; Hossain, Imtiaz; Lazic, Stanley E; Davies, John W; Zhang, Xian

    2017-07-01

    Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustment of multiple parameters. Here, we present an approach based on a multi-scale convolutional neural network (M-CNN) that classifies, in a single cohesive step, cellular images into phenotypes by using directly and solely the images' pixel intensity values. The only parameters in the approach are the weights of the neural network, which are automatically optimized based on training images. The approach requires no a priori knowledge or manual customization, and is applicable to single- or multi-channel images displaying single or multiple cells. We evaluated the classification performance of the approach on eight diverse benchmark datasets. The approach yielded overall a higher classification accuracy compared with state-of-the-art results, including those of other deep CNN architectures. In addition to using the network to simply obtain a yes-or-no prediction for a given phenotype, we use the probability outputs calculated by the network to quantitatively describe the phenotypes. This study shows that these probability values correlate with chemical treatment concentrations. This finding validates further our approach and enables chemical treatment potency estimation via CNNs. The network specifications and solver definitions are provided in Supplementary Software 1. william_jose.godinez_navarro@novartis.com or xian-1.zhang@novartis.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  4. Unique thylakoid membrane architecture of a unicellular N2-fixing cyanobacterium revealed by electron tomography.

    PubMed

    Liberton, Michelle; Austin, Jotham R; Berg, R Howard; Pakrasi, Himadri B

    2011-04-01

    Cyanobacteria, descendants of the endosymbiont that gave rise to modern-day chloroplasts, are vital contributors to global biological energy conversion processes. A thorough understanding of the physiology of cyanobacteria requires detailed knowledge of these organisms at the level of cellular architecture and organization. In these prokaryotes, the large membrane protein complexes of the photosynthetic and respiratory electron transport chains function in the intracellular thylakoid membranes. Like plants, the architecture of the thylakoid membranes in cyanobacteria has direct impact on cellular bioenergetics, protein transport, and molecular trafficking. However, whole-cell thylakoid organization in cyanobacteria is not well understood. Here we present, by using electron tomography, an in-depth analysis of the architecture of the thylakoid membranes in a unicellular cyanobacterium, Cyanothece sp. ATCC 51142. Based on the results of three-dimensional tomographic reconstructions of near-entire cells, we determined that the thylakoids in Cyanothece 51142 form a dense and complex network that extends throughout the entire cell. This thylakoid membrane network is formed from the branching and splitting of membranes and encloses a single lumenal space. The entire thylakoid network spirals as a peripheral ring of membranes around the cell, an organization that has not previously been described in a cyanobacterium. Within the thylakoid membrane network are areas of quasi-helical arrangement with similarities to the thylakoid membrane system in chloroplasts. This cyanobacterial thylakoid arrangement is an efficient means of packing a large volume of membranes in the cell while optimizing intracellular transport and trafficking.

  5. Stiffening of Red Blood Cells Induced by Cytoskeleton Disorders: A Joint Theory-Experiment Study.

    PubMed

    Lai, Lipeng; Xu, Xiaofeng; Lim, Chwee Teck; Cao, Jianshu

    2015-12-01

    The functions and elasticities of the cell are largely related to the structures of the cytoskeletons underlying the lipid bilayer. Among various cell types, the red blood cell (RBC) possesses a relatively simple cytoskeletal structure. Underneath the membrane, the RBC cytoskeleton takes the form of a two-dimensional triangular network, consisting of nodes of actins (and other proteins) and edges of spectrins. Recent experiments focusing on the malaria-infected RBCs (iRBCs) show that there is a correlation between the elongation of spectrins in the cytoskeletal network and the stiffening of the iRBCs. Here we rationalize the correlation between these two observations by combining the wormlike chain model for single spectrins and the effective medium theory for the network elasticity. We specifically focus on how the disorders in the cytoskeletal network affect its macroscopic elasticity. Analytical and numerical solutions from our model reveal that the stiffness of the membrane increases with increasing end-to-end distances of spectrins, but has a nonmonotonic dependence on the variance of the end-to-end distance distributions. These predictions are verified quantitatively by our atomic force microscopy and micropipette aspiration measurements of iRBCs. The model may, from a molecular level, provide guidelines for future identification of new treatment methods for RBC-related diseases, such as malaria infection. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  6. Protein kinase C and calcineurin cooperatively mediate cell survival under compressive mechanical stress.

    PubMed

    Mishra, Ranjan; van Drogen, Frank; Dechant, Reinhard; Oh, Soojung; Jeon, Noo Li; Lee, Sung Sik; Peter, Matthias

    2017-12-19

    Cells experience compressive stress while growing in limited space or migrating through narrow constrictions. To survive such stress, cells reprogram their intracellular organization to acquire appropriate mechanical properties. However, the mechanosensors and downstream signaling networks mediating these changes remain largely unknown. Here, we have established a microfluidic platform to specifically trigger compressive stress, and to quantitatively monitor single-cell responses of budding yeast in situ. We found that yeast senses compressive stress via the cell surface protein Mid2 and the calcium channel proteins Mid1 and Cch1, which then activate the Pkc1/Mpk1 MAP kinase pathway and calcium signaling, respectively. Genetic analysis revealed that these pathways work in parallel to mediate cell survival. Mid2 contains a short intracellular tail and a serine-threonine-rich extracellular domain with spring-like properties, and both domains are required for mechanosignaling. Mid2-dependent spatial activation of the Pkc1/Mpk1 pathway depolarizes the actin cytoskeleton in budding or shmooing cells, thereby antagonizing polarized growth to protect cells under compressive stress conditions. Together, these results identify a conserved signaling network responding to compressive mechanical stress, which, in higher eukaryotes, may ensure cell survival in confined environments.

  7. Actin protofilament orientation in deformation of the erythrocyte membrane skeleton.

    PubMed Central

    Picart, C; Dalhaimer, P; Discher, D E

    2000-01-01

    The red cell's spectrin-actin network is known to sustain local states of shear, dilation, and condensation, and yet the short actin filaments are found to maintain membrane-tangent and near-random azimuthal orientations. When calibrated with polarization results for single actin filaments, imaging of micropipette-deformed red cell ghosts has allowed an assessment of actin orientations and possible reorientations in the network. At the hemispherical cap of the aspirated projection, where the network can be dilated severalfold, filaments have the same membrane-tangent orientation as on a relatively unstrained portion of membrane. Likewise, over the length of the network projection pulled into the micropipette, where the network is strongly sheared in axial extension and circumferential contraction, actin maintains its tangent orientation and is only very weakly aligned with network extension. Similar results are found for the integral membrane protein Band 3. Allowing for thermal fluctuations, we deduce a bound for the effective coupling constant, alpha, between network shear and azimuthal orientation of the protofilament. The finding that alpha must be about an order of magnitude or more below its tight-coupling value illustrates how nanostructural kinematics can decouple from more macroscopic responses. Monte Carlo simulations of spectrin-actin networks at approximately 10-nm resolution further support this conclusion and substantiate an image of protofilaments as elements of a high-temperature spin glass. PMID:11106606

  8. Neuroblast survival depends on mature vascular network formation after mouse stroke: role of endothelial and smooth muscle progenitor cell co-administration.

    PubMed

    Nih, Lina R; Deroide, Nicolas; Leré-Déan, Carole; Lerouet, Dominique; Soustrat, Mathieu; Levy, Bernard I; Silvestre, Jean-Sébastien; Merkulova-Rainon, Tatiana; Pocard, Marc; Margaill, Isabelle; Kubis, Nathalie

    2012-04-01

    Pro-angiogenic cell-based therapies constitute an interesting and attractive approach to enhancing post-stroke neurogenesis and decreasing neurological deficit. However, most new stroke-induced neurons die during the first few weeks after ischemia, thus impairing total recovery. Although the neovascularization process involves different cell types and various growth factors, most cell therapy protocols are based on the biological effects of single-cell-type populations or on the administration of heterogeneous populations of progenitors, namely human cord blood-derived CD34(+) cells, with scarce vascular progenitor cells. Tight cooperation between endothelial cells and smooth muscle cells/pericytes is critical for the development of functional neovessels. We hypothesized that neuroblast survival in stroke brain depends on mature vascular network formation. In this study, we injected a combination of endothelial progenitor cells (EPCs) and smooth muscle progenitor cells (SMPCs), isolated from human umbilical cord blood, into a murine model of permanent focal ischemia induced by middle cerebral artery occlusion. The co-administration of SMPCs and EPCs induced enhanced angiogenesis and vascular remodeling in the peri-infarct and infarct areas, where vessels exhibited a more mature phenotype. This activation of vessel growth resulted in the maintenance of neurogenesis and neuroblast migration to the peri-ischemic cortex. Our data suggest that a mature vascular network is essential for neuroblast survival after cerebral ischemia, and that co-administration of EPCs and SMPCs may constitute a novel therapeutic strategy for improving the treatment of stroke. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  9. Boolean dynamics of genetic regulatory networks inferred from microarray time series data

    DOE PAGES

    Martin, Shawn; Zhang, Zhaoduo; Martino, Anthony; ...

    2007-01-31

    Methods available for the inference of genetic regulatory networks strive to produce a single network, usually by optimizing some quantity to fit the experimental observations. In this paper we investigate the possibility that multiple networks can be inferred, all resulting in similar dynamics. This idea is motivated by theoretical work which suggests that biological networks are robust and adaptable to change, and that the overall behavior of a genetic regulatory network might be captured in terms of dynamical basins of attraction. We have developed and implemented a method for inferring genetic regulatory networks for time series microarray data. Our methodmore » first clusters and discretizes the gene expression data using k-means and support vector regression. We then enumerate Boolean activation–inhibition networks to match the discretized data. In conclusion, the dynamics of the Boolean networks are examined. We have tested our method on two immunology microarray datasets: an IL-2-stimulated T cell response dataset and a LPS-stimulated macrophage response dataset. In both cases, we discovered that many networks matched the data, and that most of these networks had similar dynamics.« less

  10. Mass cytometry: a highly multiplexed single-cell technology for advancing drug development.

    PubMed

    Atkuri, Kondala R; Stevens, Jeffrey C; Neubert, Hendrik

    2015-02-01

    Advanced single-cell analysis technologies (e.g., mass cytometry) that help in multiplexing cellular measurements in limited-volume primary samples are critical in bridging discovery efforts to successful drug approval. Mass cytometry is the state-of-the-art technology in multiparametric single-cell analysis. Mass cytometers (also known as cytometry by time-of-flight or CyTOF) combine the cellular analysis principles of traditional fluorescence-based flow cytometry with the selectivity and quantitative power of inductively coupled plasma-mass spectrometry. Standard flow cytometry is limited in the number of parameters that can be measured owing to the overlap in signal when detecting fluorescently labeled antibodies. Mass cytometry uses antibodies tagged to stable isotopes of rare earth metals, which requires minimal signal compensation between the different metal tags. This unique feature enables researchers to seamlessly multiplex up to 40 independent measurements on single cells. In this overview we first present an overview of mass cytometry and compare it with traditional flow cytometry. We then discuss the emerging and potential applications of CyTOF technology in the pharmaceutical industry, including quantitative and qualitative deep profiling of immune cells and their applications in assessing drug immunogenicity, extensive mapping of signaling networks in single cells, cell surface receptor quantification and multiplexed internalization kinetics, multiplexing sample analysis by barcoding, and establishing cell ontologies on the basis of phenotype and/or function. We end with a discussion of the anticipated impact of this technology on drug development lifecycle with special emphasis on the utility of mass cytometry in deciphering a drug's pharmacokinetics and pharmacodynamics relationship. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

  11. Phenotype-dependent Ca(2+) dynamics in single boutons of various anatomically identified GABAergic interneurons in the rat hippocampus.

    PubMed

    Lőrincz, Tibor; Kisfali, Máté; Lendvai, Balázs; Sylvester Vizi, Elek

    2016-02-01

    Interneurons (INs) of the hippocampus exert versatile inhibition on pyramidal cells by silencing the network at different oscillation frequencies. Although IN discharge can phase-lock to various rhythms in the hippocampus, under high-frequency axon firing, the boutons may not be able to follow the fast activity. Here, we studied Ca(2+) responses to action potentials (APs) in single boutons using combined two-photon microscopy and patch clamp electrophysiology in three types of INs: non-fast-spiking (NFS) neurons showing cannabinoid 1 receptor labelling and dendrite targeting, fast-spiking partially parvalbumin-positive cells synapsing with dendrites (DFS), and parvalbumin-positive cells with perisomatic innervation (PFS). The increase in [Ca(2+) ]i from AP trains was substantially higher in NFS boutons than in DFS or PFS boutons. The decay of bouton Ca(2+) responses was markedly faster in DFS and PFS cells compared with NFS neurons. The bouton-to-bouton variability of AP-evoked Ca(2+) transients in the same axon was surprisingly low in each cell type. Importantly, local responses were saturated after shorter trains of APs in NFS cells than in PFS cells. This feature of fast-spiking neurons might allow them to follow higher-frequency gamma oscillations for a longer time than NFS cells. The function of NFS boutons may better support asynchronous GABA release. In conclusion, we demonstrate several neuron-specific Ca(2+) transients in boutons of NFS, PFS and DFS neurons, which may serve differential functions in hippocampal networks. © 2015 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  12. A network model for the specification of vulval precursor cells and cell fusion control in Caenorhabditis elegans

    PubMed Central

    Weinstein, Nathan; Mendoza, Luis

    2013-01-01

    The vulva of Caenorhabditis elegans has been long used as an experimental model of cell differentiation and organogenesis. While it is known that the signaling cascades of Wnt, Ras/MAPK, and NOTCH interact to form a molecular network, there is no consensus regarding its precise topology and dynamical properties. We inferred the molecular network, and developed a multivalued synchronous discrete dynamic model to study its behavior. The model reproduces the patterns of activation reported for the following types of cell: vulval precursor, first fate, second fate, second fate with reversed polarity, third fate, and fusion fate. We simulated the fusion of cells, the determination of the first, second, and third fates, as well as the transition from the second to the first fate. We also used the model to simulate all possible single loss- and gain-of-function mutants, as well as some relevant double and triple mutants. Importantly, we associated most of these simulated mutants to multivulva, vulvaless, egg-laying defective, or defective polarity phenotypes. The model shows that it is necessary for RAL-1 to activate NOTCH signaling, since the repression of LIN-45 by RAL-1 would not suffice for a proper second fate determination in an environment lacking DSL ligands. We also found that the model requires the complex formed by LAG-1, LIN-12, and SEL-8 to inhibit the transcription of eff-1 in second fate cells. Our model is the largest reconstruction to date of the molecular network controlling the specification of vulval precursor cells and cell fusion control in C. elegans. According to our model, the process of fate determination in the vulval precursor cells is reversible, at least until either the cells fuse with the ventral hypoderm or divide, and therefore the cell fates must be maintained by the presence of extracellular signals. PMID:23785384

  13. Interlocked positive and negative feedback network motifs regulate β-catenin activity in the adherens junction pathway

    PubMed Central

    Klinke, David J.; Horvath, Nicholas; Cuppett, Vanessa; Wu, Yueting; Deng, Wentao; Kanj, Rania

    2015-01-01

    The integrity of epithelial tissue architecture is maintained through adherens junctions that are created through extracellular homotypic protein–protein interactions between cadherin molecules. Cadherins also provide an intracellular scaffold for the formation of a multiprotein complex that contains signaling proteins, including β-catenin. Environmental factors and controlled tissue reorganization disrupt adherens junctions by cleaving the extracellular binding domain and initiating a series of transcriptional events that aim to restore tissue homeostasis. However, it remains unclear how alterations in cell adhesion coordinate transcriptional events, including those mediated by β-catenin in this pathway. Here were used quantitative single-cell and population-level in vitro assays to quantify the endogenous pathway dynamics after the proteolytic disruption of the adherens junctions. Using prior knowledge of isolated elements of the overall network, we interpreted these data using in silico model-based inference to identify the topology of the regulatory network. Collectively the data suggest that the regulatory network contains interlocked network motifs consisting of a positive feedback loop, which is used to restore the integrity of adherens junctions, and a negative feedback loop, which is used to limit β-catenin–induced gene expression. PMID:26224311

  14. Academic Honesty through Technology

    ERIC Educational Resources Information Center

    Lecher, Mark

    2005-01-01

    Over the past two decades, technology use has increased in the classroom. What started out as a single computer in a classroom has evolved into a laptop or handheld for every student, with a wireless connection to the Internet and other network resources. Cell phones, PDAs, and other electronic tools have opened up new horizons for utilizing…

  15. A Framework for Event Prioritization in Cyber Network Defense

    DTIC Science & Technology

    2014-07-15

    U.S.," Reuters (US online Edition), pp. http://www.reuters.com/article/2013/11/06/net-us-usa-china- hacking - idUSBRE9A51AN20131106, 6 Nov 2013. [2...expressed individually, or as a single vector by using the magnitude of these three factors (cell J5 in Table 5

  16. Flat bands in fractal-like geometry

    NASA Astrophysics Data System (ADS)

    Pal, Biplab; Saha, Kush

    2018-05-01

    We report the presence of multiple flat bands in a class of two-dimensional lattices formed by Sierpinski gasket (SPG) fractal geometries as the basic unit cells. Solving the tight-binding Hamiltonian for such lattices with different generations of a SPG network, we find multiple degenerate and nondegenerate completely flat bands, depending on the configuration of parameters of the Hamiltonian. Moreover, we establish a generic formula to determine the number of such bands as a function of the generation index ℓ of the fractal geometry. We show that the flat bands and their neighboring dispersive bands have remarkable features, the most interesting one being the spin-1 conical-type spectrum at the band center without any staggered magnetic flux, in contrast to the kagome lattice. We furthermore investigate the effect of magnetic flux in these lattice settings and show that different combinations of fluxes through such fractal unit cells lead to a richer spectrum with a single isolated flat band or gapless electron- or holelike flat bands. Finally, we discuss a possible experimental setup to engineer such a fractal flat-band network using single-mode laser-induced photonic waveguides.

  17. TNF-alpha inhibits insulin action in liver and adipose tissue: A model of metabolic syndrome.

    PubMed

    Solomon, S S; Odunusi, O; Carrigan, D; Majumdar, G; Kakoola, D; Lenchik, N I; Gerling, I C

    2010-02-01

    Several studies suggest that TNF-alpha contributes to the development of insulin resistance (IR). We compared transcriptional profiles of rat H-411E liver cells exposed to insulin in the absence or presence of TNF-alpha. We identified 33 genes whose expression was altered by insulin, and then reversed by TNF-alpha. Twenty-six of these 33 genes created a single network centered around: insulin, TNF-alpha, p38-MAPK, TGFb1; SMAD and STAT1; and enzymes and cytokines involved in apoptosis (CASP3, GADD45B, IL2, TNF-alpha, etc.). We analyzed our data together with other data of gene expression in adipocytes and found a number of processes common to both, for example, cell death and inflammation; intercellular signaling and metabolism; G-Protein, IL-10 and PTEN signaling. Moreover, the two datasets combined generated a single molecular network that further identified PTEN (a phosphatase) as a unique new link between insulin signaling, IR, and apoptosis reflecting the pathophysiology of "metabolic syndrome". Georg Thieme Verlag KG Stuttgart * New York.

  18. Salinomycin Hydroxamic Acids: Synthesis, Structure, and Biological Activity of Polyether Ionophore Hybrids.

    PubMed

    Borgström, Björn; Huang, Xiaoli; Chygorin, Eduard; Oredsson, Stina; Strand, Daniel

    2016-06-09

    The polyether ionophore salinomycin has recently gained attention due to its exceptional ability to selectively reduce the proportion of cancer stem cells within a number of cancer cell lines. Efficient single step strategies for the preparation of hydroxamic acid hybrids of this compound varying in N- and O-alkylation are presented. The parent hydroxamic acid, salinomycin-NHOH, forms both inclusion complexes and well-defined electroneutral complexes with potassium and sodium cations via 1,3-coordination by the hydroxamic acid moiety to the metal ion. A crystal structure of an cationic sodium complex with a noncoordinating anion corroborates this finding and, moreover, reveals a novel type of hydrogen bond network that stabilizes the head-to-tail conformation that encapsulates the cation analogously to the native structure. The hydroxamic acid derivatives display down to single digit micromolar activity against cancer cells but unlike salinomycin selective reduction of ALDH(+) cells, a phenotype associated with cancer stem cells was not observed. Mechanistic implications are discussed.

  19. Salinomycin Hydroxamic Acids: Synthesis, Structure, and Biological Activity of Polyether Ionophore Hybrids

    PubMed Central

    2016-01-01

    The polyether ionophore salinomycin has recently gained attention due to its exceptional ability to selectively reduce the proportion of cancer stem cells within a number of cancer cell lines. Efficient single step strategies for the preparation of hydroxamic acid hybrids of this compound varying in N- and O-alkylation are presented. The parent hydroxamic acid, salinomycin-NHOH, forms both inclusion complexes and well-defined electroneutral complexes with potassium and sodium cations via 1,3-coordination by the hydroxamic acid moiety to the metal ion. A crystal structure of an cationic sodium complex with a noncoordinating anion corroborates this finding and, moreover, reveals a novel type of hydrogen bond network that stabilizes the head-to-tail conformation that encapsulates the cation analogously to the native structure. The hydroxamic acid derivatives display down to single digit micromolar activity against cancer cells but unlike salinomycin selective reduction of ALDH+ cells, a phenotype associated with cancer stem cells was not observed. Mechanistic implications are discussed. PMID:27326340

  20. Resolving dynamics of cell signaling via real-time imaging of the immunological synapse.

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

    Stevens, Mark A.; Pfeiffer, Janet R.; Wilson, Bridget S.

    2009-10-01

    This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effortmore » to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.« less

  1. Efficient Steplike Carrier Multiplication in Percolative Networks of Epitaxially Connected PbSe Nanocrystals

    DOE PAGES

    Kulkarni, Aditya; Evers, Wiel H.; Tomic, Stanko; ...

    2017-12-14

    Here, carrier multiplication (CM) is a process in which a single photon excites two or more electrons. CM is of interest to enhance the efficiency of a solar cell. Until now, CM in thin films and solar cells of semiconductor nanocrystals (NCs) has been found at photon energies well above the minimum required energy of twice the band gap. The high threshold of CM strongly limits the benefits for solar cell applications. We show that CM is more efficient in a percolative network of directly connected PbSe NCs. The CM threshold is at twice the band gap and increases inmore » a steplike fashion with photon energy. A lower CM efficiency is found for a solid of weaker coupled NCs. This demonstrates that the coupling between NCs strongly affects the CM efficiency. According to device simulations, the measured CM efficiency would significantly enhance the power conversion efficiency of a solar cell.« less

  2. Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity.

    PubMed

    Zhang, J D; Berntenis, N; Roth, A; Ebeling, M

    2014-06-01

    Gene signatures of drug-induced toxicity are of broad interest, but they are often identified from small-scale, single-time point experiments, and are therefore of limited applicability. To address this issue, we performed multivariate analysis of gene expression, cell-based assays, and histopathological data in the TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system) database. Data mining highlights four genes-EGR1, ATF3, GDF15 and FGF21-that are induced 2 h after drug administration in human and rat primary hepatocytes poised to eventually undergo cytotoxicity-induced cell death. Modelling and simulation reveals that these early stress-response genes form a functional network with evolutionarily conserved structure and intrinsic dynamics. This is underlined by the fact that early induction of this network in vivo predicts drug-induced liver and kidney pathology with high accuracy. Our findings demonstrate the value of early gene-expression signatures in predicting and understanding compound-induced toxicity. The identified network can empower first-line tests that reduce animal use and costs of safety evaluation.

  3. Network Topologies and Dynamics Leading to Endotoxin Tolerance and Priming in Innate Immune Cells

    NASA Astrophysics Data System (ADS)

    Fu, Yan; Glaros, Trevor; Zhu, Meng; Wang, Ping; Wu, Zhanghan; Tyson, John; Li, Liwu; Xing, Jianhua

    2012-01-01

    The innate immune system, acting as the first line of host defense, senses and adapts to foreign challenges through complex intracellular and intercellular signaling networks. Endotoxin tolerance and priming elicited by macrophages are classic examples of the complex adaptation of innate immune cells. Upon repetitive exposures to different doses of bacterial endotoxin (lipopolysaccharide) or other stimulants, macrophages show either suppressed or augmented inflammatory responses compared to a single exposure to the stimulant. Endotoxin tolerance and priming are critically involved in both immune homeostasis and the pathogenesis of diverse inflammatory diseases. However, the underlying molecular mechanisms are not well understood. By means of a computational search through the parameter space of a coarse-grained three-node network with a two-stage Metropolis sampling approach, we enumerated all the network topologies that can generate priming or tolerance. We discovered three major mechanisms for priming (pathway synergy, suppressor deactivation, activator induction) and one for tolerance (inhibitor persistence). These results not only explain existing experimental observations, but also reveal intriguing test scenarios for future experimental studies to clarify mechanisms of endotoxin priming and tolerance.

  4. Scale dependence of the mechanics of active gels with increasing motor concentration.

    PubMed

    Sonn-Segev, Adar; Bernheim-Groswasser, Anne; Roichman, Yael

    2017-10-18

    Actin is a protein that plays an essential role in maintaining the mechanical integrity of cells. In response to strong external stresses, it can assemble into large bundles, but it grows into a fine branched network to induce cell motion. In some cases, the self-organization of actin fibers and networks involves the action of bipolar filaments of the molecular motor myosin. Such self-organization processes mediated by large myosin bipolar filaments have been studied extensively in vitro. Here we create active gels, composed of single actin filaments and small myosin bipolar filaments. The active steady state in these gels persists long enough to enable the characterization of their mechanical properties using one and two point microrheology. We study the effect of myosin concentration on the mechanical properties of this model system for active matter, for two different motor assembly sizes. In contrast to previous studies of networks with large motor assemblies, we find that the fluctuations of tracer particles embedded in the network decrease in amplitude as motor concentration increases. Nonetheless, we show that myosin motors stiffen the actin networks, in accordance with bulk rheology measurements of networks containing larger motor assemblies. This implies that such stiffening is of universal nature and may be relevant to a wider range of cytoskeleton-based structures.

  5. Translational models of tumor angiogenesis: A nexus of in silico and in vitro models.

    PubMed

    Soleimani, Shirin; Shamsi, Milad; Ghazani, Mehran Akbarpour; Modarres, Hassan Pezeshgi; Valente, Karolina Papera; Saghafian, Mohsen; Ashani, Mehdi Mohammadi; Akbari, Mohsen; Sanati-Nezhad, Amir

    2018-03-05

    Emerging evidence shows that endothelial cells are not only the building blocks of vascular networks that enable oxygen and nutrient delivery throughout a tissue but also serve as a rich resource of angiocrine factors. Endothelial cells play key roles in determining cancer progression and response to anti-cancer drugs. Furthermore, the endothelium-specific deposition of extracellular matrix is a key modulator of the availability of angiocrine factors to both stromal and cancer cells. Considering tumor vascular network as a decisive factor in cancer pathogenesis and treatment response, these networks need to be an inseparable component of cancer models. Both computational and in vitro experimental models have been extensively developed to model tumor-endothelium interactions. While informative, they have been developed in different communities and do not yet represent a comprehensive platform. In this review, we overview the necessity of incorporating vascular networks for both in vitro and in silico cancer models and discuss recent progresses and challenges of in vitro experimental microfluidic cancer vasculature-on-chip systems and their in silico counterparts. We further highlight how these two approaches can merge together with the aim of presenting a predictive combinatorial platform for studying cancer pathogenesis and testing the efficacy of single or multi-drug therapeutics for cancer treatment. Copyright © 2018. Published by Elsevier Inc.

  6. Cytoskeletal mechanics: Structure and Dynamics

    NASA Astrophysics Data System (ADS)

    Bausch, Andreas

    2008-03-01

    The actin cytoskeleton, a dynamic network of semiflexible filaments and associated regulatory proteins, is responsible for the extraordinary viscoelastic properties of cells. Especially for cellular motility the controlled self assembly to defined structures and the dynamic reorganization on different time scales are of outstanding importance. A prominent example for the controlled self assembly are actin bundles: in many cytoskeletal processes cells rely on the tight control of the structural and mechanical properties of the actin bundles. Using an in vitro model system we show that size control relies on a mismatch between the helical structure of individual actin filaments and the packing symmetry within bundles. While such self assembled structure may evoke the picture of a static network the contrary is the case: the cytoskeleton is highly dynamic and a constant remodeling takes place in vivo. Such dynamic reorganization of the cytoskeleton relies on the non-static nature of single actin/ABP bonds. Here, we study the thermal and forced unbinding events of individual ABP in such in vitro networks. The binding kinetics of the transient crosslinkers determines the mechanical response of such networks -- in the linear as well in the non-linear regime. These effects are important prerequisites for the high adaptability of cells and at the same time might be the molecular mechanism employed by them for mechanosensing.

  7. Human cerebral organoids recapitulate gene expression programs of fetal neocortex development

    PubMed Central

    Camp, J. Gray; Badsha, Farhath; Florio, Marta; Kanton, Sabina; Gerber, Tobias; Wilsch-Bräuninger, Michaela; Lewitus, Eric; Sykes, Alex; Hevers, Wulf; Lancaster, Madeline; Knoblich, Juergen A.; Lachmann, Robert; Pääbo, Svante; Huttner, Wieland B.; Treutlein, Barbara

    2015-01-01

    Cerebral organoids—3D cultures of human cerebral tissue derived from pluripotent stem cells—have emerged as models of human cortical development. However, the extent to which in vitro organoid systems recapitulate neural progenitor cell proliferation and neuronal differentiation programs observed in vivo remains unclear. Here we use single-cell RNA sequencing (scRNA-seq) to dissect and compare cell composition and progenitor-to-neuron lineage relationships in human cerebral organoids and fetal neocortex. Covariation network analysis using the fetal neocortex data reveals known and previously unidentified interactions among genes central to neural progenitor proliferation and neuronal differentiation. In the organoid, we detect diverse progenitors and differentiated cell types of neuronal and mesenchymal lineages and identify cells that derived from regions resembling the fetal neocortex. We find that these organoid cortical cells use gene expression programs remarkably similar to those of the fetal tissue to organize into cerebral cortex-like regions. Our comparison of in vivo and in vitro cortical single-cell transcriptomes illuminates the genetic features underlying human cortical development that can be studied in organoid cultures. PMID:26644564

  8. An integrated cell-free metabolic platform for protein production and synthetic biology

    PubMed Central

    Jewett, Michael C; Calhoun, Kara A; Voloshin, Alexei; Wuu, Jessica J; Swartz, James R

    2008-01-01

    Cell-free systems offer a unique platform for expanding the capabilities of natural biological systems for useful purposes, i.e. synthetic biology. They reduce complexity, remove structural barriers, and do not require the maintenance of cell viability. Cell-free systems, however, have been limited by their inability to co-activate multiple biochemical networks in a single integrated platform. Here, we report the assessment of biochemical reactions in an Escherichia coli cell-free platform designed to activate natural metabolism, the Cytomim system. We reveal that central catabolism, oxidative phosphorylation, and protein synthesis can be co-activated in a single reaction system. Never before have these complex systems been shown to be simultaneously activated without living cells. The Cytomim system therefore promises to provide the metabolic foundation for diverse ab initio cell-free synthetic biology projects. In addition, we describe an improved Cytomim system with enhanced protein synthesis yields (up to 1200 mg/l in 2 h) and lower costs to facilitate production of protein therapeutics and biochemicals that are difficult to make in vivo because of their toxicity, complexity, or unusual cofactor requirements. PMID:18854819

  9. Innate responses to gene knockouts impact overlapping gene networks and vary with respect to resistance to viral infection.

    PubMed

    Liu, Yonghong; Liu, Yuanyuan; Wu, Jiaming; Roizman, Bernard; Zhou, Grace Guoying

    2018-04-03

    Analyses of the levels of mRNAs encoding IFIT1, IFI16, RIG-1, MDA5, CXCL10, LGP2, PUM1, LSD1, STING, and IFNβ in cell lines from which the gene encoding LGP2, LSD1, PML, HDAC4, IFI16, PUM1, STING, MDA5, IRF3, or HDAC 1 had been knocked out, as well as the ability of these cell lines to support the replication of HSV-1, revealed the following: ( i ) Cell lines lacking the gene encoding LGP2, PML, or HDAC4 (cluster 1) exhibited increased levels of expression of partially overlapping gene networks. Concurrently, these cell lines produced from 5 fold to 12 fold lower yields of HSV-1 than the parental cells. ( ii ) Cell lines lacking the genes encoding STING, LSD1, MDA5, IRF3, or HDAC 1 (cluster 2) exhibited decreased levels of mRNAs of partially overlapping gene networks. Concurrently, these cell lines produced virus yields that did not differ from those produced by the parental cell line. The genes up-regulated in cell lines forming cluster 1, overlapped in part with genes down-regulated in cluster 2. The key conclusions are that gene knockouts and subsequent selection for growth causes changes in expression of multiple genes, and hence the phenotype of the cell lines cannot be ascribed to a single gene; the patterns of gene expression may be shared by multiple knockouts; and the enhanced immunity to viral replication by cluster 1 knockout cell lines but not by cluster 2 cell lines suggests that in parental cells, the expression of innate resistance to infection is specifically repressed.

  10. A protein interaction network analysis for yeast integral membrane protein.

    PubMed

    Shi, Ming-Guang; Huang, De-Shuang; Li, Xue-Ling

    2008-01-01

    Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

  11. Graphene Quantum Dots Interfaced with Single Bacterial Spore for Bio-Electromechanical Devices: A Graphene Cytobot

    PubMed Central

    Sreeprasad, T. S.; Nguyen, Phong; Alshogeathri, Ahmed; Hibbeler, Luke; Martinez, Fabian; McNeil, Nolan; Berry, Vikas

    2015-01-01

    The nanoarchitecture and micromachinery of a cell can be leveraged to fabricate sophisticated cell-driven devices. This requires a coherent strategy to derive cell's mechanistic abilities, microconstruct, and chemical-texture towards such microtechnologies. For example, a microorganism's hydrophobic membrane encapsulating hygroscopic constituents allows it to sustainably withhold a high aquatic pressure. Further, it provides a rich surface chemistry available for nano-interfacing and a strong mechanical response to humidity. Here we demonstrate a route to incorporate a complex cellular structure into microelectromechanics by interfacing compatible graphene quantum dots (GQDs) with a highly responsive single spore microstructure. A sensitive and reproducible electron-tunneling width modulation of 1.63 nm within a network of GQDs chemically-secured on a spore was achieved via sporal hydraulics with a driving force of 299.75 Torrs (21.7% water at GQD junctions). The electron-transport activation energy and the Coulomb blockade threshold for the GQD network were 35 meV and 31 meV, respectively; while the inter-GQD capacitance increased by 1.12 folds at maximum hydraulic force. This is the first example of nano/bio interfacing with spores and will lead to the evolution of next-generation bio-derived microarchitectures, probes for cellular/biochemical processes, biomicrorobotic-mechanisms, and membranes for micromechanical actuation. PMID:25774962

  12. Advanced Fault Diagnosis Methods in Molecular Networks

    PubMed Central

    Habibi, Iman; Emamian, Effat S.; Abdi, Ali

    2014-01-01

    Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally. PMID:25290670

  13. Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks

    PubMed Central

    Pena, Rodrigo F. O.; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C.; Lindner, Benjamin

    2018-01-01

    Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as indicated by comparison with simulation results of large recurrent networks. Our method can help to elucidate how network heterogeneity shapes the asynchronous state in recurrent neural networks. PMID:29551968

  14. Multiscale modelling of Flow-Induced Blood Cell Damage

    NASA Astrophysics Data System (ADS)

    Liu, Yaling; Sohrabi, Salman

    2017-11-01

    We study red blood cell (RBC) damage and hemolysis at cellular level. Under high shear rates, pores form on RBC membranes through which hemoglobin (Hb) leaks out and increases free Hb content of plasma leading to hemolysis. By coupling lattice Boltzmann and spring connected network models through immersed boundary method, we estimate hemolysis of a single RBC under various shear rates. The developed cellular damage model can be used as a predictive tool for hydrodynamic and hematologic design optimization of blood-wetting medical devices.

  15. Controlling the Flow of Visual Information through the Lateral Geniculate Nucleus: From Single Cells to Neural Networks.

    DTIC Science & Technology

    1991-10-31

    in my laboratory, Drs. Dan Kammen, Ernst Niebur and Florentin Worg6tter, as well as with three outside collaborators, Prof. John Kulli from the...also for experimentally observed cortical column structures ( Niebur and Worg6tter, 1990a,b). Temporal Dynamics of Interacting Neuronal Populations We...Connection Machine to simulate a 128 by 128 grid of 16,384 cells under a variety of stimulation patterns ( Niebur , Kammen & Koch, 1991). To explore

  16. Single-Cell Sequencing of the Healthy and Diseased Heart Reveals Ckap4 as a New Modulator of Fibroblasts Activation.

    PubMed

    Gladka, Monika M; Molenaar, Bas; de Ruiter, Hesther; van der Elst, Stefan; Tsui, Hoyee; Versteeg, Danielle; Lacraz, Grègory P A; Huibers, Manon M H; van Oudenaarden, Alexander; van Rooij, Eva

    2018-01-31

    Background -Genome-wide transcriptome analysis has greatly advanced our understanding of the regulatory networks underlying basic cardiac biology and mechanisms driving disease. However, so far, the resolution of studying gene expression patterns in the adult heart has been limited to the level of extracts from whole tissues. The use of tissue homogenates inherently causes the loss of any information on cellular origin or cell type-specific changes in gene expression. Recent developments in RNA amplification strategies provide a unique opportunity to use small amounts of input RNA for genome-wide sequencing of single cells. Methods -Here, we present a method to obtain high quality RNA from digested cardiac tissue from adult mice for automated single-cell sequencing of both the healthy and diseased heart. Results -After optimization, we were able to perform single-cell sequencing on adult cardiac tissue under both homeostatic conditions and after ischemic injury. Clustering analysis based on differential gene expression unveiled known and novel markers of all main cardiac cell types. Based on differential gene expression we were also able to identify multiple subpopulations within a certain cell type. Furthermore, applying single-cell sequencing on both the healthy and the injured heart indicated the presence of disease-specific cell subpopulations. As such, we identified cytoskeleton associated protein 4 ( Ckap4 ) as a novel marker for activated fibroblasts that positively correlates with known myofibroblast markers in both mouse and human cardiac tissue. Ckap4 inhibition in activated fibroblasts treated with TGFβ triggered a greater increase in the expression of genes related to activated fibroblasts compared to control, suggesting a role of Ckap4 in modulating fibroblast activation in the injured heart. Conclusions -Single-cell sequencing on both the healthy and diseased adult heart allows us to study transcriptomic differences between cardiac cells, as well as cell type-specific changes in gene expression during cardiac disease. This new approach provides a wealth of novel insights into molecular changes that underlie the cellular processes relevant for cardiac biology and pathophysiology. Applying this technology could lead to the discovery of new therapeutic targets relevant for heart disease.

  17. Stochastic loss and gain of symmetric divisions in the C. elegans epidermis perturbs robustness of stem cell number

    PubMed Central

    Katsanos, Dimitris; Koneru, Sneha L.; Mestek Boukhibar, Lamia; Gritti, Nicola; Ghose, Ritobrata; Appleford, Peter J.; Doitsidou, Maria; Woollard, Alison; van Zon, Jeroen S.; Poole, Richard J.

    2017-01-01

    Biological systems are subject to inherent stochasticity. Nevertheless, development is remarkably robust, ensuring the consistency of key phenotypic traits such as correct cell numbers in a certain tissue. It is currently unclear which genes modulate phenotypic variability, what their relationship is to core components of developmental gene networks, and what is the developmental basis of variable phenotypes. Here, we start addressing these questions using the robust number of Caenorhabditis elegans epidermal stem cells, known as seam cells, as a readout. We employ genetics, cell lineage tracing, and single molecule imaging to show that mutations in lin-22, a Hes-related basic helix-loop-helix (bHLH) transcription factor, increase seam cell number variability. We show that the increase in phenotypic variability is due to stochastic conversion of normally symmetric cell divisions to asymmetric and vice versa during development, which affect the terminal seam cell number in opposing directions. We demonstrate that LIN-22 acts within the epidermal gene network to antagonise the Wnt signalling pathway. However, lin-22 mutants exhibit cell-to-cell variability in Wnt pathway activation, which correlates with and may drive phenotypic variability. Our study demonstrates the feasibility to study phenotypic trait variance in tractable model organisms using unbiased mutagenesis screens. PMID:29108019

  18. 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.

  19. Hypoxia induces a phase transition within a kinase signaling network in cancer cells.

    PubMed

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B; Shin, Young Shik; Mischel, Paul S; Levine, R D; Heath, James R

    2013-04-09

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)--a critical component of hypoxic signaling and a compelling cancer drug target--is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier's principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles.

  20. The Effect of Single Pyramidal Neuron Firing Within Layer 2/3 and Layer 4 in Mouse V1.

    PubMed

    Meyer, Jochen F; Golshani, Peyman; Smirnakis, Stelios M

    2018-01-01

    The influence of cortical cell spiking activity on nearby cells has been studied extensively in vitro . Less is known, however, about the impact of single cell firing on local cortical networks in vivo . In a pioneering study, Kwan and Dan (Kwan and Dan, 2012) reported that in mouse layer 2/3 (L2/3), under anesthesia , stimulating a single pyramidal cell recruits ~2.1% of neighboring units. Here we employ two-photon calcium imaging in layer 2/3 of mouse V1, in conjunction with single-cell patch clamp stimulation in layer 2/3 or layer 4, to probe, in both the awake and lightly anesthetized states , how (i) activating single L2/3 pyramidal neurons recruits neighboring units within L2/3 and from layer 4 (L4) to L2/3, and whether (ii) activating single pyramidal neurons changes population activity in local circuit. To do this, it was essential to develop an algorithm capable of quantifying how sensitive the calcium signal is at detecting effectively recruited units ("followers"). This algorithm allowed us to estimate the chance of detecting a follower as a function of the probability that an epoch of stimulation elicits one extra action potential (AP) in the follower cell. Using this approach, we found only a small fraction (<0.75%) of L2/3 cells to be significantly activated within a radius of ~200 μm from a stimulated neighboring L2/3 pyramidal cell. This fraction did not change significantly in the awake vs. the lightly anesthetized state, nor when stimulating L2/3 vs. underlying L4 pyramidal neurons. These numbers are in general agreement with, though lower than, the percentage of neighboring cells (2.1% pyramidal cells and interneurons combined) reported by Kwan and Dan to be activated upon stimulating single L2/3 pyramidal neurons under anesthesia (Kwan and Dan, 2012). Interestingly, despite the small number of individual units found to be reliably driven, we did observe a modest but significant elevation in aggregate population responses compared to sham stimulation. This underscores the distributed impact that single cell stimulation has on neighboring microcircuit responses, revealing only a small minority of relatively strongly connected partners. Patch-clamp stimulation in conjunction with 2-photon imaging shows that activating single layer-2/3 or layer-4 pyramidal neurons produces few (<1% of local units) reliable single-cell followers in L2/3 of mouse area V1, either under light anesthesia or in quiet wakefulness: instead, single cell stimulation was found to elevate aggregate population activity in a weak but highly distributed fashion.

  1. Synchronizing stochastic circadian oscillators in single cells of Neurospora crassa

    NASA Astrophysics Data System (ADS)

    Deng, Zhaojie; Arsenault, Sam; Caranica, Cristian; Griffith, James; Zhu, Taotao; Al-Omari, Ahmad; Schüttler, Heinz-Bernd; Arnold, Jonathan; Mao, Leidong

    2016-10-01

    The synchronization of stochastic coupled oscillators is a central problem in physics and an emerging problem in biology, particularly in the context of circadian rhythms. Most measurements on the biological clock are made at the macroscopic level of millions of cells. Here measurements are made on the oscillators in single cells of the model fungal system, Neurospora crassa, with droplet microfluidics and the use of a fluorescent recorder hooked up to a promoter on a clock controlled gene-2 (ccg-2). The oscillators of individual cells are stochastic with a period near 21 hours (h), and using a stochastic clock network ensemble fitted by Markov Chain Monte Carlo implemented on general-purpose graphical processing units (or GPGPUs) we estimated that >94% of the variation in ccg-2 expression was stochastic (as opposed to experimental error). To overcome this stochasticity at the macroscopic level, cells must synchronize their oscillators. Using a classic measure of similarity in cell trajectories within droplets, the intraclass correlation (ICC), the synchronization surface ICC is measured on >25,000 cells as a function of the number of neighboring cells within a droplet and of time. The synchronization surface provides evidence that cells communicate, and synchronization varies with genotype.

  2. Synchronizing stochastic circadian oscillators in single cells of Neurospora crassa

    PubMed Central

    Deng, Zhaojie; Arsenault, Sam; Caranica, Cristian; Griffith, James; Zhu, Taotao; Al-Omari, Ahmad; Schüttler, Heinz-Bernd; Arnold, Jonathan; Mao, Leidong

    2016-01-01

    The synchronization of stochastic coupled oscillators is a central problem in physics and an emerging problem in biology, particularly in the context of circadian rhythms. Most measurements on the biological clock are made at the macroscopic level of millions of cells. Here measurements are made on the oscillators in single cells of the model fungal system, Neurospora crassa, with droplet microfluidics and the use of a fluorescent recorder hooked up to a promoter on a clock controlled gene-2 (ccg-2). The oscillators of individual cells are stochastic with a period near 21 hours (h), and using a stochastic clock network ensemble fitted by Markov Chain Monte Carlo implemented on general-purpose graphical processing units (or GPGPUs) we estimated that >94% of the variation in ccg-2 expression was stochastic (as opposed to experimental error). To overcome this stochasticity at the macroscopic level, cells must synchronize their oscillators. Using a classic measure of similarity in cell trajectories within droplets, the intraclass correlation (ICC), the synchronization surface ICC is measured on >25,000 cells as a function of the number of neighboring cells within a droplet and of time. The synchronization surface provides evidence that cells communicate, and synchronization varies with genotype. PMID:27786253

  3. Bidirectional global spontaneous network activity precedes the canonical unidirectional circuit organization in the developing hippocampus.

    PubMed

    Shi, Yulin; Ikrar, Taruna; Olivas, Nicholas D; Xu, Xiangmin

    2014-06-15

    Spontaneous network activity is believed to sculpt developing neural circuits. Spontaneous giant depolarizing potentials (GDPs) were first identified with single-cell recordings from rat CA3 pyramidal neurons, but here we identify and characterize a large-scale spontaneous network activity we term global network activation (GNA) in the developing mouse hippocampal slices, which is measured macroscopically by fast voltage-sensitive dye imaging. The initiation and propagation of GNA in the mouse is largely GABA-independent and dominated by glutamatergic transmission via AMPA receptors. Despite the fact that signal propagation in the adult hippocampus is strongly unidirectional through the canonical trisynaptic circuit (dentate gyrus [DG] to CA3 to CA1), spontaneous GNA in the developing hippocampus originates in distal CA3 and propagates both forward to CA1 and backward to DG. Photostimulation-evoked GNA also shows prominent backward propagation in the developing hippocampus from CA3 to DG. Mouse GNA is strongly correlated to electrophysiological recordings of highly localized single-cell and local field potential events. Photostimulation mapping of neural circuitry demonstrates that the enhancement of local circuit connections to excitatory pyramidal neurons occurs over the same time course as GNA and reveals the underlying pathways accounting for GNA backward propagation from CA3 to DG. The disappearance of GNA coincides with a transition to the adult-like unidirectional circuit organization at about 2 weeks of age. Taken together, our findings strongly suggest a critical link between GNA activity and maturation of functional circuit connections in the developing hippocampus. Copyright © 2013 Wiley Periodicals, Inc.

  4. Network representations of immune system complexity

    PubMed Central

    Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

    2015-01-01

    The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

  5. Protein complexes and functional modules in molecular networks

    NASA Astrophysics Data System (ADS)

    Spirin, Victor; Mirny, Leonid A.

    2003-10-01

    Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

  6. Network and neuronal membrane properties in hybrid networks reciprocally regulate selectivity to rapid thalamocortical inputs.

    PubMed

    Pesavento, Michael J; Pinto, David J

    2012-11-01

    Rapidly changing environments require rapid processing from sensory inputs. Varying deflection velocities of a rodent's primary facial vibrissa cause varying temporal neuronal activity profiles within the ventral posteromedial thalamic nucleus. Local neuron populations in a single somatosensory layer 4 barrel transform sparsely coded input into a spike count based on the input's temporal profile. We investigate this transformation by creating a barrel-like hybrid network with whole cell recordings of in vitro neurons from a cortical slice preparation, embedding the biological neuron in the simulated network by presenting virtual synaptic conductances via a conductance clamp. Utilizing the hybrid network, we examine the reciprocal network properties (local excitatory and inhibitory synaptic convergence) and neuronal membrane properties (input resistance) by altering the barrel population response to diverse thalamic input. In the presence of local network input, neurons are more selective to thalamic input timing; this arises from strong feedforward inhibition. Strongly inhibitory (damping) network regimes are more selective to timing and less selective to the magnitude of input but require stronger initial input. Input selectivity relies heavily on the different membrane properties of excitatory and inhibitory neurons. When inhibitory and excitatory neurons had identical membrane properties, the sensitivity of in vitro neurons to temporal vs. magnitude features of input was substantially reduced. Increasing the mean leak conductance of the inhibitory cells decreased the network's temporal sensitivity, whereas increasing excitatory leak conductance enhanced magnitude sensitivity. Local network synapses are essential in shaping thalamic input, and differing membrane properties of functional classes reciprocally modulate this effect.

  7. Magnetic pattern at supergranulation scale: the void size distribution

    NASA Astrophysics Data System (ADS)

    Berrilli, F.; Scardigli, S.; Del Moro, D.

    2014-08-01

    The large-scale magnetic pattern observed in the photosphere of the quiet Sun is dominated by the magnetic network. This network, created by photospheric magnetic fields swept into convective downflows, delineates the boundaries of large-scale cells of overturning plasma and exhibits "voids" in magnetic organization. These voids include internetwork fields, which are mixed-polarity sparse magnetic fields that populate the inner part of network cells. To single out voids and to quantify their intrinsic pattern we applied a fast circle-packing-based algorithm to 511 SOHO/MDI high-resolution magnetograms acquired during the unusually long solar activity minimum between cycles 23 and 24. The computed void distribution function shows a quasi-exponential decay behavior in the range 10-60 Mm. The lack of distinct flow scales in this range corroborates the hypothesis of multi-scale motion flows at the solar surface. In addition to the quasi-exponential decay, we have found that the voids depart from a simple exponential decay at about 35 Mm.

  8. From Saccharomyces cerevisiae to human: The important gene co-expression modules.

    PubMed

    Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

    2017-08-01

    Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

  9. Functional Single-Walled Carbon Nanotubes and Nanoengineered Networks for Organic- and Perovskite-Solar-Cell Applications.

    PubMed

    Barbero, David R; Stranks, Samuel D

    2016-11-01

    Carbon nanotubes have a variety of remarkable electronic and mechanical properties that, in principle, lend them to promising optoelectronic applications. However, the field has been plagued by heterogeneity in the distributions of synthesized tubes and uncontrolled bundling, both of which have prevented nanotubes from reaching their full potential. Here, a variety of recently demonstrated solution-processing avenues is presented, which may combat these challenges through manipulation of nanoscale structures. Recent advances in polymer-wrapping of single-walled carbon nanotubes (SWNTs) are shown, along with how the resulting nanostructures can selectively disperse tubes while also exploiting the favorable properties of the polymer, such as light-harvesting ability. New methods to controllably form nanoengineered SWNT networks with controlled nanotube placement are discussed. These nanoengineered networks decrease bundling, lower the percolation threshold, and enable a strong enhancement in charge conductivity compared to random networks, making them potentially attractive for optoelectronic applications. Finally, SWNT applications, to date, in organic and perovskite photovoltaics are reviewed, and insights as to how the aforementioned recent advancements can lead to improved device performance provided. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. White blood cell differential count of maturation stages in bone marrow smear using dual-stage convolutional neural networks.

    PubMed

    Choi, Jin Woo; Ku, Yunseo; Yoo, Byeong Wook; Kim, Jung-Ah; Lee, Dong Soon; Chai, Young Jun; Kong, Hyoun-Joong; Kim, Hee Chan

    2017-01-01

    The white blood cell differential count of the bone marrow provides information concerning the distribution of immature and mature cells within maturation stages. The results of such examinations are important for the diagnosis of various diseases and for follow-up care after chemotherapy. However, manual, labor-intensive methods to determine the differential count lead to inter- and intra-variations among the results obtained by hematologists. Therefore, an automated system to conduct the white blood cell differential count is highly desirable, but several difficulties hinder progress. There are variations in the white blood cells of each maturation stage, small inter-class differences within each stage, and variations in images because of the different acquisition and staining processes. Moreover, a large number of classes need to be classified for bone marrow smear analysis, and the high density of touching cells in bone marrow smears renders difficult the segmentation of single cells, which is crucial to traditional image processing and machine learning. Few studies have attempted to discriminate bone marrow cells, and even these have either discriminated only a few classes or yielded insufficient performance. In this study, we propose an automated white blood cell differential counting system from bone marrow smear images using a dual-stage convolutional neural network (CNN). A total of 2,174 patch images were collected for training and testing. The dual-stage CNN classified images into 10 classes of the myeloid and erythroid maturation series, and achieved an accuracy of 97.06%, a precision of 97.13%, a recall of 97.06%, and an F-1 score of 97.1%. The proposed method not only showed high classification performance, but also successfully classified raw images without single cell segmentation and manual feature extraction by implementing CNN. Moreover, it demonstrated rotation and location invariance. These results highlight the promise of the proposed method as an automated white blood cell differential count system.

  11. White blood cell differential count of maturation stages in bone marrow smear using dual-stage convolutional neural networks

    PubMed Central

    Choi, Jin Woo; Ku, Yunseo; Yoo, Byeong Wook; Kim, Jung-Ah; Lee, Dong Soon; Chai, Young Jun; Kong, Hyoun-Joong

    2017-01-01

    The white blood cell differential count of the bone marrow provides information concerning the distribution of immature and mature cells within maturation stages. The results of such examinations are important for the diagnosis of various diseases and for follow-up care after chemotherapy. However, manual, labor-intensive methods to determine the differential count lead to inter- and intra-variations among the results obtained by hematologists. Therefore, an automated system to conduct the white blood cell differential count is highly desirable, but several difficulties hinder progress. There are variations in the white blood cells of each maturation stage, small inter-class differences within each stage, and variations in images because of the different acquisition and staining processes. Moreover, a large number of classes need to be classified for bone marrow smear analysis, and the high density of touching cells in bone marrow smears renders difficult the segmentation of single cells, which is crucial to traditional image processing and machine learning. Few studies have attempted to discriminate bone marrow cells, and even these have either discriminated only a few classes or yielded insufficient performance. In this study, we propose an automated white blood cell differential counting system from bone marrow smear images using a dual-stage convolutional neural network (CNN). A total of 2,174 patch images were collected for training and testing. The dual-stage CNN classified images into 10 classes of the myeloid and erythroid maturation series, and achieved an accuracy of 97.06%, a precision of 97.13%, a recall of 97.06%, and an F-1 score of 97.1%. The proposed method not only showed high classification performance, but also successfully classified raw images without single cell segmentation and manual feature extraction by implementing CNN. Moreover, it demonstrated rotation and location invariance. These results highlight the promise of the proposed method as an automated white blood cell differential count system. PMID:29228051

  12. Fibrin Networks Support Recurring Mechanical Loads by Adapting their Structure across Multiple Scales.

    PubMed

    Kurniawan, Nicholas A; Vos, Bart E; Biebricher, Andreas; Wuite, Gijs J L; Peterman, Erwin J G; Koenderink, Gijsje H

    2016-09-06

    Tissues and cells sustain recurring mechanical loads that span a wide range of loading amplitudes and timescales as a consequence of exposure to blood flow, muscle activity, and external impact. Both tissues and cells derive their mechanical strength from fibrous protein scaffolds, which typically have a complex hierarchical structure. In this study, we focus on a prototypical hierarchical biomaterial, fibrin, which is one of the most resilient naturally occurring biopolymers and forms the structural scaffold of blood clots. We show how fibrous networks composed of fibrin utilize irreversible changes in their hierarchical structure at different scales to maintain reversible stress stiffening up to large strains. To trace the origin of this paradoxical resilience, we systematically tuned the microstructural parameters of fibrin and used a combination of optical tweezers and fluorescence microscopy to measure the interactions of single fibrin fibers for the first time, to our knowledge. We demonstrate that fibrin networks adapt to moderate strains by remodeling at the network scale through the spontaneous formation of new bonds between fibers, whereas they adapt to high strains by plastic remodeling of the fibers themselves. This multiscale adaptation mechanism endows fibrin gels with the remarkable ability to sustain recurring loads due to shear flows and wound stretching. Our findings therefore reveal a microscopic mechanism by which tissues and cells can balance elastic nonlinearity and plasticity, and thus can provide microstructural insights into cell-driven remodeling of tissues. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  13. 3D quantitative phase imaging of neural networks using WDT

    NASA Astrophysics Data System (ADS)

    Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel

    2015-03-01

    White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

  14. Isolating Attention Systems: A Cognitive-Anatomical Analysis. Cognitive Science Program, Technical Report No. 86-3.

    ERIC Educational Resources Information Center

    Posner, Michael I.; And Others

    Recently, knowledge of the mechanisms of visual-spatial attention has improved due to studies employing single cell recording with alert monkeys and studies using performance analysis of neurological patients. These studies suggest that a complex neural network including parts of the posterior parietal lobe and midbrain are involved in covert…

  15. A biological approach to assembling tissue modules through endothelial capillary network formation.

    PubMed

    Riesberg, Jeremiah J; Shen, Wei

    2015-09-01

    To create functional tissues having complex structures, bottom-up approaches to assembling small tissue modules into larger constructs have been emerging. Most of these approaches are based on chemical reactions or physical interactions at the interface between tissue modules. Here we report a biological assembly approach to integrate small tissue modules through endothelial capillary network formation. When adjacent tissue modules contain appropriate extracellular matrix materials and cell types that support robust endothelial capillary network formation, capillary tubules form and grow across the interface, resulting in assembly of the modules into a single, larger construct. It was shown that capillary networks formed in modules of dense fibrin gels seeded with human umbilical vein endothelial cells (HUVECs) and mesenchymal stem cells (MSCs); adjacent modules were firmly assembled into an integrated construct having a strain to failure of 117 ± 26%, a tensile strength of 2208 ± 83 Pa and a Young's modulus of 2548 ± 574 Pa. Under the same culture conditions, capillary networks were absent in modules of dense fibrin gels seeded with either HUVECs or MSCs alone; adjacent modules disconnected even when handled gently. This biological assembly approach eliminates the need for chemical reactions or physical interactions and their associated limitations. In addition, the integrated constructs are prevascularized, and therefore this bottom-up assembly approach may also help address the issue of vascularization, another key challenge in tissue engineering. Copyright © 2015 John Wiley & Sons, Ltd.

  16. Chimeric green fluorescent protein-aequorin as bioluminescent Ca2+ reporters at the single-cell level

    PubMed Central

    Baubet, Valérie; Le Mouellic, Hervé; Campbell, Anthony K.; Lucas-Meunier, Estelle; Fossier, Philippe; Brûlet, Philippe

    2000-01-01

    Monitoring calcium fluxes in real time could help to understand the development, the plasticity, and the functioning of the central nervous system. In jellyfish, the chemiluminescent calcium binding aequorin protein is associated with the green fluorescent protein and a green bioluminescent signal is emitted upon Ca2+ stimulation. We decided to use this chemiluminescence resonance energy transfer between the two molecules. Calcium-sensitive bioluminescent reporter genes have been constructed by fusing green fluorescent protein and aequorin, resulting in much more light being emitted. Chemiluminescent and fluorescent activities of these fusion proteins have been assessed in mammalian cells. Cytosolic Ca2+ increases were imaged at the single-cell level with a cooled intensified charge-coupled device camera. This bifunctional reporter gene should allow the investigation of calcium activities in neuronal networks and in specific subcellular compartments in transgenic animals. PMID:10860991

  17. The phenotype of cancer cell invasion controlled by fibril diameter and pore size of 3D collagen networks.

    PubMed

    Sapudom, Jiranuwat; Rubner, Stefan; Martin, Steve; Kurth, Tony; Riedel, Stefanie; Mierke, Claudia T; Pompe, Tilo

    2015-06-01

    The behavior of cancer cells is strongly influenced by the properties of extracellular microenvironments, including topology, mechanics and composition. As topological and mechanical properties of the extracellular matrix are hard to access and control for in-depth studies of underlying mechanisms in vivo, defined biomimetic in vitro models are needed. Herein we show, how pore size and fibril diameter of collagen I networks distinctively regulate cancer cell morphology and invasion. Three-dimensional collagen I matrices with a tight control of pore size, fibril diameter and stiffness were reconstituted by adjustment of concentration and pH value during matrix reconstitution. At first, a detailed analysis of topology and mechanics of matrices using confocal laser scanning microscopy, image analysis tools and force spectroscopy indicate pore size and not fibril diameter as the major determinant of matrix elasticity. Secondly, by using two different breast cancer cell lines (MDA-MB-231 and MCF-7), we demonstrate collagen fibril diameter--and not pore size--to primarily regulate cell morphology, cluster formation and invasion. Invasiveness increased and clustering decreased with increasing fibril diameter for both, the highly invasive MDA-MB-231 cells with mesenchymal migratory phenotype and the MCF-7 cells with amoeboid migratory phenotype. As this behavior was independent of overall pore size, matrix elasticity is shown to be not the major determinant of the cell characteristics. Our work emphasizes the complex relationship between structural-mechanical properties of the extracellular matrix and invasive behavior of cancer cells. It suggests a correlation of migratory and invasive phenotype of cancer cells in dependence on topological and mechanical features of the length scale of single fibrils and not on coarse-grained network properties. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Cell differentiation modeled via a coupled two-switch regulatory network

    NASA Astrophysics Data System (ADS)

    Schittler, D.; Hasenauer, J.; Allgöwer, F.; Waldherr, S.

    2010-12-01

    Mesenchymal stem cells can give rise to bone and other tissue cells, but their differentiation still escapes full control. In this paper we address this issue by mathematical modeling. We present a model for a genetic switch determining the cell fate of progenitor cells which can differentiate into osteoblasts (bone cells) or chondrocytes (cartilage cells). The model consists of two switch mechanisms and reproduces the experimentally observed three stable equilibrium states: a progenitor, an osteogenic, and a chondrogenic state. Conventionally, the loss of an intermediate (progenitor) state and the entailed attraction to one of two opposite (differentiated) states is modeled as a result of changing parameters. In our model in contrast, we achieve this by distributing the differentiation process to two functional switch parts acting in concert: one triggering differentiation and the other determining cell fate. Via stability and bifurcation analysis, we investigate the effects of biochemical stimuli associated with different system inputs. We employ our model to generate differentiation scenarios on the single cell as well as on the cell population level. The single cell scenarios allow to reconstruct the switching upon extrinsic signals, whereas the cell population scenarios provide a framework to identify the impact of intrinsic properties and the limiting factors for successful differentiation.

  19. A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions

    PubMed Central

    2013-01-01

    Background Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Results Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia before. Lactate fermentation is one of the key themes discussed in the field of hypoxia; however, malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate, which are connected by a single pathway, may provide a more significant marker of hypoxia in cancer. Conclusions Metabolic networks generated for each cell line were compared to identify conserved metabolite pathway responses to low oxygen environments. Furthermore, we believe this methodology will have general application within metabolomics. PMID:24153255

  20. Neural networks distinguish between taste qualities based on receptor cell population responses.

    PubMed

    Varkevisser, B; Peterson, D; Ogura, T; Kinnamon, S C

    2001-06-01

    Response features of taste receptor cell action potentials were examined using an artificial neural network to determine whether they contain information about taste quality. Using the loose patch technique to record from hamster taste buds in vivo we recorded population responses of single fungiform papillae to NaCl (100 mM), sucrose (200 mM) and the synthetic sweetener NC-00274-01 (NC-01) (200 microM). Features of each response describing both burst and inter-burst characteristics were then presented to an artificial neural network for pairwise classification of taste stimuli. Responses to NaCl could be distinguished from those to both NC-01 and sucrose with accuracies of up to 86%. In contrast, pairwise comparisons between sucrose and NC-01 were not successful, scoring at chance (50%). Also, comparisons between two different concentrations of NaCl, 0.01 and 0.005 M, scored at chance. Pairwise comparisons using only those features that relate to the inter-burst behavior of the response (i.e. bursting rate) did not hinder the performance of the neural network as both sweeteners versus NaCl received scores of 75--85%. Comparisons using features corresponding to each individual burst scored poorly, receiving scores only slightly above chance. We then compared the sweeteners with varying concentrations of NaCl (0.1, 0.01, 0.005 and 0.001 M) using only those features corresponding to bursting rate within a 1 s time window. The neural network was capable of distinguishing between NaCl and NC-01 at all concentrations tested; while comparisons between NaCl and sucrose received high scores at all concentrations except 0.001 M. These results show that two different taste qualities can be distinguished from each other based solely on the bursting rates of action potentials in single taste buds and that this distinction is independent of stimulation intensity down to 0.001 M NaCl. These data suggest that action potentials in taste receptor cells may play a role in taste quality coding.

  1. MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data.

    PubMed

    Sella, Nadir; Verny, Louis; Uguzzoni, Guido; Affeldt, Séverine; Isambert, Hervé

    2018-07-01

    We present a web server running the MIIC algorithm, a network learning method combining constraint-based and information-theoretic frameworks to reconstruct causal, non-causal or mixed networks from non-perturbative data, without the need for an a priori choice on the class of reconstructed network. Starting from a fully connected network, the algorithm first removes dispensable edges by iteratively subtracting the most significant information contributions from indirect paths between each pair of variables. The remaining edges are then filtered based on their confidence assessment or oriented based on the signature of causality in observational data. MIIC online server can be used for a broad range of biological data, including possible unobserved (latent) variables, from single-cell gene expression data to protein sequence evolution and outperforms or matches state-of-the-art methods for either causal or non-causal network reconstruction. MIIC online can be freely accessed at https://miic.curie.fr. Supplementary data are available at Bioinformatics online.

  2. Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

    PubMed Central

    Li, Chang-Lin; Li, Kai-Cheng; Wu, Dan; Chen, Yan; Luo, Hao; Zhao, Jing-Rong; Wang, Sa-Shuang; Sun, Ming-Ming; Lu, Ying-Jin; Zhong, Yan-Qing; Hu, Xu-Ye; Hou, Rui; Zhou, Bei-Bei; Bao, Lan; Xiao, Hua-Sheng; Zhang, Xu

    2016-01-01

    Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion (DRG) by high-coverage single-cell RNA-sequencing (10 950 ± 1 218 genes per neuron) and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors (MHNs). Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors (MNs) expressing BAI1-associated protein 2-like 1 (Baiap2l1). Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap2l1-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases. PMID:26691752

  3. Design of a hybrid power system based on solar cell and vibration energy harvester

    NASA Astrophysics Data System (ADS)

    Zhang, Bin; Li, Mingxue; Zhong, Shaoxuan; He, Zhichao; Zhang, Yufeng

    2018-03-01

    Power source has become a serious restriction of wireless sensor network. High efficiency, self-energized and long-life renewable source is the optimum solution for unmanned sensor network applications. However, single renewable power source can be easily affected by ambient environment, which influences stability of the system. In this work, a hybrid power system consists of a solar panel, a vibration energy harvester and a lithium battery is demonstrated. The system is able to harvest multiple types of ambient energy, which extends its applicability and feasibility. Experiments have been conducted to verify performance of the system.

  4. Vitamin E-loaded dialyzer resets PBMC-operated cytokine network in dialysis patients.

    PubMed

    Libetta, Carmelo; Zucchi, Manuela; Gori, Elena; Sepe, Vincenzo; Galli, Francesco; Meloni, Federica; Milanesi, Fabio; Dal Canton, Antonio

    2004-04-01

    In hemodialysis patients the activity of stimulated Th1 lymphocytes is depressed, while Th2 cells are constitutively primed. Such phenomena may depend on monocyte activation and altered release of interleukin (IL)-12 and IL-18, which regulate Th cell differentiation. Reactive oxygen species (ROS) activate monocytes; therefore, a hemodialyzer with antioxidant activity would contrast ROS, prevent monocyte activation, reset IL-12 and IL-18 release, and restore Th1/Th2 balance. Ten patients on regular dialysis treatment (RDT) with cellulosic membrane (CM) were shifted to vitamin E-coated dialyzer (VE). During treatment with CM and after 3, 6, and 12 months of treatment with VE, peripheral blood mononuclear cells (PBMC) and purified CD4+ cells were isolated, and cultured, resting, mitogen-stimulated, and interferon gamma (IFNgamma), IL-4, IL-10, IL-12, and IL-18 release was measured. Vitamin E and A plasma levels and the effects of a single dialysis session on peripheral blood NO levels were assayed. The constitutive release of IL-4 and IL-10 by CD4+ cells was abated significantly by treatment with VE (nadir -77.8% and -55.3%, respectively, at 12 months). INFgamma release by mitogen-stimulated CD4+ recovered with VE (zenith +501% at 12 months). PBMC constitutive production of IL-12 and IL-18 was significantly reduced by VE (nadir at 12 months -64.7% and -51.3%, respectively). VE increased plasma levels of vitamins E and A. NO plasma levels fell after a single dialysis treatment with VE (-17%, P < 0.05) in contrast with CU (+27.1%, P < 0.05). The network of cytokines released by monocytes and Th cells is reset toward normality by treatment with vitamin E-coated dialyzer.

  5. Tropomodulin 1 Regulation of Actin Is Required for the Formation of Large Paddle Protrusions Between Mature Lens Fiber Cells.

    PubMed

    Cheng, Catherine; Nowak, Roberta B; Biswas, Sondip K; Lo, Woo-Kuen; FitzGerald, Paul G; Fowler, Velia M

    2016-08-01

    To elucidate the proteins required for specialized small interlocking protrusions and large paddle domains at lens fiber cell tricellular junctions (vertices), we developed a novel method to immunostain single lens fibers and studied changes in cell morphology due to loss of tropomodulin 1 (Tmod1), an F-actin pointed end-capping protein. We investigated F-actin and F-actin-binding protein localization in interdigitations of Tmod1+/+ and Tmod1-/- single mature lens fibers. F-actin-rich small protrusions and large paddles were present along cell vertices of Tmod1+/+ mature fibers. In contrast, Tmod1-/- mature fiber cells lack normal paddle domains, while small protrusions were unaffected. In Tmod1+/+ mature fibers, Tmod1, β2-spectrin, and α-actinin are localized in large puncta in valleys between paddles; but in Tmod1-/- mature fibers, β2-spectrin was dispersed while α-actinin was redistributed at the base of small protrusions and rudimentary paddles. Fimbrin and Arp3 (actin-related protein 3) were located in puncta at the base of small protrusions, while N-cadherin and ezrin outlined the cell membrane in both Tmod1+/+ and Tmod1-/- mature fibers. These results suggest that distinct F-actin organizations are present in small protrusions versus large paddles. Formation and/or maintenance of large paddle domains depends on a β2-spectrin-actin network stabilized by Tmod1. α-Actinin-crosslinked F-actin bundles are enhanced in absence of Tmod1, indicating altered cytoskeleton organization. Formation of small protrusions is likely facilitated by Arp3-branched and fimbrin-bundled F-actin networks, which do not depend on Tmod1. This is the first work to reveal the F-actin-associated proteins required for the formation of paddles between lens fibers.

  6. Booster dose after 10 years is recommended following 17DD-YF primary vaccination.

    PubMed

    Campi-Azevedo, Ana Carolina; Costa-Pereira, Christiane; Antonelli, Lis R; Fonseca, Cristina T; Teixeira-Carvalho, Andréa; Villela-Rezende, Gabriela; Santos, Raiany A; Batista, Maurício A; Campos, Fernanda M; Pacheco-Porto, Luiza; Melo Júnior, Otoni A; Hossell, Débora M S H; Coelho-dos-Reis, Jordana G; Peruhype-Magalhães, Vanessa; Costa-Silva, Matheus F; de Oliveira, Jaquelline G; Farias, Roberto H; Noronha, Tatiana G; Lemos, Jandira A; von Doellinger, Vanessa dos R; Simões, Marisol; de Souza, Mirian M; Malaquias, Luiz C; Persi, Harold R; Pereira, Jorge M; Martins, José A; Dornelas-Ribeiro, Marcos; Vinhas, Aline de A; Alves, Tatiane R; Maia, Maria de L; Freire, Marcos da S; Martins, Reinaldo de M; Homma, Akira; Romano, Alessandro P M; Domingues, Carla M; Tauil, Pedro L; Vasconcelos, Pedro F; Rios, Maria; Caldas, Iramaya R; Camacho, Luiz A; Martins-Filho, Olindo Assis

    2016-01-01

    A single vaccination of Yellow Fever vaccines is believed to confer life-long protection. In this study, results of vaccinees who received a single dose of 17DD-YF immunization followed over 10 y challenge this premise. YF-neutralizing antibodies, subsets of memory T and B cells as well as cytokine-producing lymphocytes were evaluated in groups of adults before (NVday0) and after (PVday30-45, PVyear1-4, PVyear5-9, PVyear10-11, PVyear12-13) 17DD-YF primary vaccination. YF-neutralizing antibodies decrease significantly from PVyear1-4 to PVyear12-13 as compared to PVday30-45, and the seropositivity rates (PRNT≥2.9Log10mIU/mL) become critical (lower than 90%) beyond PVyear5-9. YF-specific memory phenotypes (effector T-cells and classical B-cells) significantly increase at PVday30-45 as compared to naïve baseline. Moreover, these phenotypes tend to decrease at PVyear10-11 as compared to PVday30-45. Decreasing levels of TNF-α(+) and IFN-γ(+) produced by CD4(+) and CD8(+) T-cells along with increasing levels of IL-10(+)CD4(+)T-cells were characteristic of anti-YF response over time. Systems biology profiling represented by hierarchic networks revealed that while the naïve baseline is characterized by independent micro-nets, primary vaccinees displayed an imbricate network with essential role of central and effector CD8(+) memory T-cell responses. Any putative limitations of this cross-sectional study will certainly be answered by the ongoing longitudinal population-based investigation. Overall, our data support the current Brazilian national immunization policy guidelines that recommend one booster dose 10 y after primary 17DD-YF vaccination.

  7. Nanostructured cavity devices for extracellular stimulation of HL-1 cells.

    PubMed

    Czeschik, Anna; Rinklin, Philipp; Derra, Ulrike; Ullmann, Sabrina; Holik, Peter; Steltenkamp, Siegfried; Offenhäusser, Andreas; Wolfrum, Bernhard

    2015-01-01

    Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network.

  8. Intrinsic bursting of AII amacrine cells underlies oscillations in the rd1 mouse retina.

    PubMed

    Choi, Hannah; Zhang, Lei; Cembrowski, Mark S; Sabottke, Carl F; Markowitz, Alexander L; Butts, Daniel A; Kath, William L; Singer, Joshua H; Riecke, Hermann

    2014-09-15

    In many forms of retinal degeneration, photoreceptors die but inner retinal circuits remain intact. In the rd1 mouse, an established model for blinding retinal diseases, spontaneous activity in the coupled network of AII amacrine and ON cone bipolar cells leads to rhythmic bursting of ganglion cells. Since such activity could impair retinal and/or cortical responses to restored photoreceptor function, understanding its nature is important for developing treatments of retinal pathologies. Here we analyzed a compartmental model of the wild-type mouse AII amacrine cell to predict that the cell's intrinsic membrane properties, specifically, interacting fast Na and slow, M-type K conductances, would allow its membrane potential to oscillate when light-evoked excitatory synaptic inputs were withdrawn following photoreceptor degeneration. We tested and confirmed this hypothesis experimentally by recording from AIIs in a slice preparation of rd1 retina. Additionally, recordings from ganglion cells in a whole mount preparation of rd1 retina demonstrated that activity in AIIs was propagated unchanged to elicit bursts of action potentials in ganglion cells. We conclude that oscillations are not an emergent property of a degenerated retinal network. Rather, they arise largely from the intrinsic properties of a single retinal interneuron, the AII amacrine cell. Copyright © 2014 the American Physiological Society.

  9. Teaching the bioinformatics of signaling networks: an integrated approach to facilitate multi-disciplinary learning.

    PubMed

    Korcsmaros, Tamas; Dunai, Zsuzsanna A; Vellai, Tibor; Csermely, Peter

    2013-09-01

    The number of bioinformatics tools and resources that support molecular and cell biology approaches is continuously expanding. Moreover, systems and network biology analyses are accompanied more and more by integrated bioinformatics methods. Traditional information-centered university teaching methods often fail, as (1) it is impossible to cover all existing approaches in the frame of a single course, and (2) a large segment of the current bioinformation can become obsolete in a few years. Signaling network offers an excellent example for teaching bioinformatics resources and tools, as it is both focused and complex at the same time. Here, we present an outline of a university bioinformatics course with four sample practices to demonstrate how signaling network studies can integrate biochemistry, genetics, cell biology and network sciences. We show that several bioinformatics resources and tools, as well as important concepts and current trends, can also be integrated to signaling network studies. The research-type hands-on experiences we show enable the students to improve key competences such as teamworking, creative and critical thinking and problem solving. Our classroom course curriculum can be re-formulated as an e-learning material or applied as a part of a specific training course. The multi-disciplinary approach and the mosaic setup of the course have the additional benefit to support the advanced teaching of talented students.

  10. Penium margaritaceum as a model organism for cell wall analysis of expanding plant cells.

    PubMed

    Rydahl, Maja G; Fangel, Jonatan U; Mikkelsen, Maria Dalgaard; Johansen, I Elisabeth; Andreas, Amanda; Harholt, Jesper; Ulvskov, Peter; Jørgensen, Bodil; Domozych, David S; Willats, William G T

    2015-01-01

    The growth of a plant cell encompasses a complex set of subcellular components interacting in a highly coordinated fashion. Ultimately, these activities create specific cell wall structural domains that regulate the prime force of expansion, internally generated turgor pressure. The precise organization of the polymeric networks of the cell wall around the protoplast also contributes to the direction of growth, the shape of the cell, and the proper positioning of the cell in a tissue. In essence, plant cell expansion represents the foundation of development. Most studies of plant cell expansion have focused primarily upon late divergent multicellular land plants and specialized cell types (e.g., pollen tubes, root hairs). Here, we describe a unicellular green alga, Penium margaritaceum (Penium), which can serve as a valuable model organism for understanding cell expansion and the underlying mechanics of the cell wall in a single plant cell.

  11. Successful choice behavior is associated with distinct and coherent network states in anterior cingulate cortex

    PubMed Central

    Lapish, Christopher C.; Durstewitz, Daniel; Chandler, L. Judson; Seamans, Jeremy K.

    2008-01-01

    Successful decision making requires an ability to monitor contexts, actions, and outcomes. The anterior cingulate cortex (ACC) is thought to be critical for these functions, monitoring and guiding decisions especially in challenging situations involving conflict and errors. A number of different single-unit correlates have been observed in the ACC that reflect the diverse cognitive components involved. Yet how ACC neurons function as an integrated network is poorly understood. Here we show, using advanced population analysis of multiple single-unit recordings from the rat ACC during performance of an ecologically valid decision-making task, that ensembles of neurons move through different coherent and dissociable states as the cognitive requirements of the task change. This organization into distinct network patterns with respect to both firing-rate changes and correlations among units broke down during trials with numerous behavioral errors, especially at choice points of the task. These results point to an underlying functional organization into cell assemblies in the ACC that may monitor choices, outcomes, and task contexts, thus tracking the animal's progression through “task space.” PMID:18708525

  12. Mechanisms of fate decision and lineage commitment during haematopoiesis.

    PubMed

    Cvejic, Ana

    2016-03-01

    Blood stem cells need to both perpetuate themselves (self-renew) and differentiate into all mature blood cells to maintain blood formation throughout life. However, it is unclear how the underlying gene regulatory network maintains this population of self-renewing and differentiating stem cells and how it accommodates the transition from a stem cell to a mature blood cell. Our current knowledge of transcriptomes of various blood cell types has mainly been advanced by population-level analysis. However, a population of seemingly homogenous blood cells may include many distinct cell types with substantially different transcriptomes and abilities to make diverse fate decisions. Therefore, understanding the cell-intrinsic differences between individual cells is necessary for a deeper understanding of the molecular basis of their behaviour. Here we review recent single-cell studies in the haematopoietic system and their contribution to our understanding of the mechanisms governing cell fate choices and lineage commitment.

  13. A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.

    PubMed

    Şenbabaoğlu, Yasin; Sümer, Selçuk Onur; Sánchez-Vega, Francisco; Bemis, Debra; Ciriello, Giovanni; Schultz, Nikolaus; Sander, Chris

    2016-02-01

    Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network; and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair; and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer.

  14. Posttranscriptional (Re)programming of Cell Fate: Examples in Stem Cells, Progenitor, and Differentiated Cells.

    PubMed

    Kanellopoulou, Chrysi; Muljo, Stefan A

    2018-01-01

    How a single genome can give rise to many different transcriptomes and thus all the different cell lineages in the human body is a fundamental question in biology. While signaling pathways, transcription factors, and chromatin architecture, to name a few determinants, have been established to play critical roles, recently, there is a growing appreciation of the roles of non-coding RNAs and RNA-binding proteins in controlling cell fates posttranscriptionally. Thus, it is vital that these emerging players are also integrated into models of gene regulatory networks that underlie programs of cellular differentiation. Sometimes, we can leverage knowledge about such posttranscriptional circuits to reprogram patterns of gene expression in meaningful ways. Here, we review three examples from our work.

  15. Holographic deep learning for rapid optical screening of anthrax spores

    PubMed Central

    Jo, YoungJu; Park, Sangjin; Jung, JaeHwang; Yoon, Jonghee; Joo, Hosung; Kim, Min-hyeok; Kang, Suk-Jo; Choi, Myung Chul; Lee, Sang Yup; Park, YongKeun

    2017-01-01

    Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and subgenus specificity. The unique “representation learning” capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis, as demonstrated for the diagnosis of Listeria monocytogenes, without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate point-of-care diagnosis of pathogens. PMID:28798957

  16. Next-generation mammalian genetics toward organism-level systems biology.

    PubMed

    Susaki, Etsuo A; Ukai, Hideki; Ueda, Hiroki R

    2017-01-01

    Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. The process begins with introduction of double-strand breaks into genomic DNA by using site-specific endonucleases, which results in highly efficient genome editing in mammalian zygotes or embryonic stem cells. By using nuclease-mediated genome editing in zygotes, or ~100% embryonic stem cell-derived mouse technology, whole-body knock-out and knock-in mice can be produced within a single generation. These emerging technologies allow us to produce multiple knock-out or knock-in strains in high-throughput manner. In this review, we discuss the basic concepts and related technologies as well as current challenges and future opportunities for next-generation mammalian genetics in organism-level systems biology.

  17. Emergent Lévy behavior in single-cell stochastic gene expression

    NASA Astrophysics Data System (ADS)

    Jia, Chen; Zhang, Michael Q.; Qian, Hong

    2017-10-01

    Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the Lévy limit provides a theoretical foundation for an empirical equation proposed in N. Friedman et al., Phys. Rev. Lett. 97, 168302 (2006), 10.1103/PhysRevLett.97.168302. Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.

  18. Use of FEC coding to improve statistical multiplexing performance for video transport over ATM networks

    NASA Astrophysics Data System (ADS)

    Kurceren, Ragip; Modestino, James W.

    1998-12-01

    The use of forward error-control (FEC) coding, possibly in conjunction with ARQ techniques, has emerged as a promising approach for video transport over ATM networks for cell-loss recovery and/or bit error correction, such as might be required for wireless links. Although FEC provides cell-loss recovery capabilities it also introduces transmission overhead which can possibly cause additional cell losses. A methodology is described to maximize the number of video sources multiplexed at a given quality of service (QoS), measured in terms of decoded cell loss probability, using interlaced FEC codes. The transport channel is modelled as a block interference channel (BIC) and the multiplexer as single server, deterministic service, finite buffer supporting N users. Based upon an information-theoretic characterization of the BIC and large deviation bounds on the buffer overflow probability, the described methodology provides theoretically achievable upper limits on the number of sources multiplexed. Performance of specific coding techniques using interlaced nonbinary Reed-Solomon (RS) codes and binary rate-compatible punctured convolutional (RCPC) codes is illustrated.

  19. MreB-Dependent Organization of the E. coli Cytoplasmic Membrane Controls Membrane Protein Diffusion.

    PubMed

    Oswald, Felix; Varadarajan, Aravindan; Lill, Holger; Peterman, Erwin J G; Bollen, Yves J M

    2016-03-08

    The functional organization of prokaryotic cell membranes, which is essential for many cellular processes, has been challenging to analyze due to the small size and nonflat geometry of bacterial cells. Here, we use single-molecule fluorescence microscopy and three-dimensional quantitative analyses in live Escherichia coli to demonstrate that its cytoplasmic membrane contains microdomains with distinct physical properties. We show that the stability of these microdomains depends on the integrity of the MreB cytoskeletal network underneath the membrane. We explore how the interplay between cytoskeleton and membrane affects trans-membrane protein (TMP) diffusion and reveal that the mobility of the TMPs tested is subdiffusive, most likely caused by confinement of TMP mobility by the submembranous MreB network. Our findings demonstrate that the dynamic architecture of prokaryotic cell membranes is controlled by the MreB cytoskeleton and regulates the mobility of TMPs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Multiple network interface core apparatus and method

    DOEpatents

    Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

    2011-04-26

    A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

  1. Hypoxia induces a phase transition within a kinase signaling network in cancer cells

    PubMed Central

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B.; Shin, Young Shik; Mischel, Paul S.; Levine, R. D.; Heath, James R.

    2013-01-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  2. Two-photon imaging of spatially extended neuronal network dynamics with high temporal resolution.

    PubMed

    Lillis, Kyle P; Eng, Alfred; White, John A; Mertz, Jerome

    2008-07-30

    We describe a simple two-photon fluorescence imaging strategy, called targeted path scanning (TPS), to monitor the dynamics of spatially extended neuronal networks with high spatiotemporal resolution. Our strategy combines the advantages of mirror-based scanning, minimized dead time, ease of implementation, and compatibility with high-resolution low-magnification objectives. To demonstrate the performance of TPS, we monitor the calcium dynamics distributed across an entire juvenile rat hippocampus (>1.5mm), at scan rates of 100 Hz, with single cell resolution and single action potential sensitivity. Our strategy for fast, efficient two-photon microscopy over spatially extended regions provides a particularly attractive solution for monitoring neuronal population activity in thick tissue, without sacrificing the signal-to-noise ratio or high spatial resolution associated with standard two-photon microscopy. Finally, we provide the code to make our technique generally available.

  3. scEpath: Energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data.

    PubMed

    Jin, Suoqin; MacLean, Adam L; Peng, Tao; Nie, Qing

    2018-02-05

    Single-cell RNA-sequencing (scRNA-seq) offers unprecedented resolution for studying cellular decision-making processes. Robust inference of cell state transition paths and probabilities is an important yet challenging step in the analysis of these data. Here we present scEpath, an algorithm that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories. We quantify the energy landscape using "single-cell energy" and distance-based measures, and find that the combination of these enables robust inference of the transition probabilities and lineage relationships between cell states. We also identify marker genes and gene expression patterns associated with cell state transitions. Our approach produces pseudotemporal orderings that are - in combination - more robust and accurate than current methods, and offers higher resolution dynamics of the cell state transitions, leading to new insight into key transition events during differentiation and development. Moreover, scEpath is robust to variation in the size of the input gene set, and is broadly unsupervised, requiring few parameters to be set by the user. Applications of scEpath led to the identification of a cell-cell communication network implicated in early human embryo development, and novel transcription factors important for myoblast differentiation. scEpath allows us to identify common and specific temporal dynamics and transcriptional factor programs along branched lineages, as well as the transition probabilities that control cell fates. A MATLAB package of scEpath is available at https://github.com/sqjin/scEpath. qnie@uci.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

  4. Quantitative Detection of Low-Abundance Transcripts at Single-Cell Level in Human Epidermal Keratinocytes by Digital Droplet Reverse Transcription-Polymerase Chain Reaction.

    PubMed

    Auvré, Frédéric; Coutier, Julien; Martin, Michèle T; Fortunel, Nicolas O

    2018-05-08

    Genetic and epigenetic characterization of the large cellular diversity observed within tissues is essential to understanding the molecular networks that ensure the regulation of homeostasis, repair, and regeneration, but also pathophysiological processes. Skin is composed of multiple cell lineages and is therefore fully concerned by this complexity. Even within one particular lineage, such as epidermal keratinocytes, different immaturity statuses or differentiation stages are represented, which are still incompletely characterized. Accordingly, there is presently great demand for methods and technologies enabling molecular investigation at single-cell level. Also, most current methods used to analyze gene expression at RNA level, such as RT-qPCR, do not directly provide quantitative data, but rather comparative ratios between two conditions. A second important need in skin biology is thus to determine the number of RNA molecules in a given cell sample. Here, we describe a workflow that we have set up to meet these specific needs, by means of transcript quantification in cellular micro-samples using flow cytometry sorting and reverse transcription-digital droplet polymerase chain reaction. As a proof-of-principle, the workflow was tested for the detection of transcription factor transcripts expressed at low levels in keratinocyte precursor cells. A linear correlation was found between quantification values and keratinocyte input numbers in a low quantity range from 40 cells to 1 cell. Interpretable signals were repeatedly obtained from single-cell samples corresponding to estimated expression levels as low as 10-20 transcript copies per keratinocyte or less. The present workflow may have broad applications for the detection and quantification of low-abundance nucleic acid species in single cells, opening up perspectives for the study of cell-to-cell genetic and molecular heterogeneity. Interestingly, the process described here does not require internal references such as house-keeping gene expression, as it is initiated with defined cell numbers, precisely sorted by flow cytometry.

  5. Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system.

    PubMed

    Ma, Xiaofeng; Kohashi, Tsunehiko; Carlson, Bruce A

    2013-07-01

    Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.

  6. Absolute Configuration of Andrographolide and Its Proliferation of Osteoblast Cell Lines

    NASA Astrophysics Data System (ADS)

    Chantrapromma, S.; Boonnak, N.; Pitakpornpreecha, T.; Yordthong, T.; Chidan Kumar, C. S.; Fun, H. K.

    2018-05-01

    Andrographolide, C20H30O5, is a labdane diterpenoid which was isolated from the leave of Andrographis paniculata. Its crystal structure is determined by single crystal X-ray diffraction: monoclinic, sp. gr. P21, Z = 2. Absolute configuration is determined by the refinement of the Flack parameter to 0.21(19). In the crystal, molecules are linked by O-H···O hydrogen bonds and C-H···O interactions into two dimensional network parallel to the (001) plane. Its proliferation of osteoblast cell lines is reported.

  7. Single CA3 pyramidal cells trigger sharp waves in vitro by exciting interneurones.

    PubMed

    Bazelot, Michaël; Teleńczuk, Maria T; Miles, Richard

    2016-05-15

    The CA3 hippocampal region generates sharp waves (SPW), a population activity associated with neuronal representations. The synaptic mechanisms responsible for the generation of these events still require clarification. Using slices maintained in an interface chamber, we found that the firing of single CA3 pyramidal cells triggers SPW like events at short latencies, similar to those for the induction of firing in interneurons. Multi-electrode records from the CA3 stratum pyramidale showed that pyramidal cells triggered events consisting of putative interneuron spikes followed by field IPSPs. SPW fields consisted of a repetition of these events at intervals of 4-8 ms. Although many properties of induced and spontaneous SPWs were similar, the triggered events tended to be initiated close to the stimulated cell. These data show that the initiation of SPWs in vitro is mediated via pyramidal cell synapses that excite interneurons. They do not indicate why interneuron firing is repeated during a SPW. Sharp waves (SPWs) are a hippocampal population activity that has been linked to neuronal representations. We show that SPWs in the CA3 region of rat hippocampal slices can be triggered by the firing of single pyramidal cells. Single action potentials in almost one-third of pyramidal cells initiated SPWs at latencies of 2-5 ms with probabilities of 0.07-0.76. Initiating pyramidal cells evoked field IPSPs (fIPSPs) at similar latencies when SPWs were not initiated. Similar spatial profiles for fIPSPs and middle components of SPWs suggested that SPW fields reflect repeated fIPSPs. Multiple extracellular records showed that the initiated SPWs tended to start near the stimulated pyramidal cell, whereas spontaneous SPWs could emerge at multiple sites. Single pyramidal cells could initiate two to six field IPSPs with distinct amplitude distributions, typically preceeded by a short-duration extracellular action potential. Comparison of these initiated fields with spontaneously occurring inhibitory field motifs allowed us to identify firing in different interneurones during the spread of SPWs. Propagation away from an initiating pyramidal cell was typically associated with the recruitment of interneurones and field IPSPs that were not activated by the stimulated pyramidal cell. SPW fields initiated by single cells were less variable than spontaneous events, suggesting that more stereotyped neuronal ensembles were activated, although neither the spatial profiles of fields, nor the identities of interneurone firing were identical for initiated events. The effects of single pyramidal cell on network events are thus mediated by different sequences of interneurone firing. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

  8. Modeling the emergence of circadian rhythms in a clock neuron network.

    PubMed

    Diambra, Luis; Malta, Coraci P

    2012-01-01

    Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

  9. Immunological network analysis in HPV associated head and neck squamous cancer and implications for disease prognosis.

    PubMed

    Chen, Xiaohang; Yan, Bingqing; Lou, Huihuang; Shen, Zhenji; Tong, Fangjia; Zhai, Aixia; Wei, Lanlan; Zhang, Fengmin

    2018-04-01

    Human papillomavirus-positive (HPV+) head and neck squamous cell cancer (HNSCC) exhibits a better prognosis than HPV-negative (HPV-) HNSCC. This difference may in part be due to enhanced immune activation in the HPV+ HNSCC tumor microenvironment. To characterize differences in immune activation between HPV+ and HPV- HNSCC tumors, we identified and annotated differentially expressed genes based upon mRNA expression data from The Cancer Genome Atlas (TCGA). Immune network between immune cells and cytokines was constructed by using single sample Gene Set Enrichment Analysis and conditional mutual information. Multivariate Cox regression analysis was used to determine the prognostic value of immune microenvironment characterization. A total of 1673 differentially expressed genes were functionally annotated. We found that genes upregulated in HPV+ HNSCC are enriched in immune-associated processes. And the up-regulated gene sets were validated by Gene Set Enrichment Analysis. The microenvironment of HPV+ HNSCC exhibited greater numbers of infiltrating B and T cells and fewer neutrophils than HPV- HNSCC. These findings were validated by two independent datasets in the Gene Expression Omnibus (GEO) database. Further analyses of T cell subtypes revealed that cytotoxic T cell subtypes predominated in HPV+ HNSCC. In addition, the ratio of M1/M2 macrophages was much higher in HPV+ HNSCC. The infiltration of these immune cells was correlated with differentially expressed cytokine-associated genes. Enhanced infiltration of B cells and CD8+ T cells were identified as independent protective factors, while high neutrophil infiltration was a risk enhancing factor for HPV+ HNSCC patients. A schematic model of immunological network was established for HPV+ HNSCC to summarize our findings. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Investigating Molecular Level Stress-Strain Relationships in Entangled F-Actin Networks by Combined Force-Measuring Optical Tweezers and Fluorescence Microscopy

    NASA Astrophysics Data System (ADS)

    Lee, Kent; Henze, Dean; Robertson-Anderson, Rae

    2013-03-01

    Actin is an important cytoskeletal protein involved in cell structure and motility, cancer invasion and metastasis, and muscle contraction. The intricate viscoelastic properties of filamentous actin (F-actin) networks allow for the many dynamic roles of actin, thus warranting investigation. Exploration of this unique stress-strain/strain-rate relationship in complex F-actin networks can also improve biomimetic materials engineering. Here, we use optical tweezers with fluorescence microscopy to study the viscoelastic properties of F-actin networks on the microscopic level. Optically trapped microspheres embedded in various F-actin networks are moved through the network using a nanoprecision piezoelectric stage. The force exerted on the microspheres by the F-actin network and subsequent force relaxation are measured, while a fraction of the filaments in the network are fluorescent-labeled to observe filament deformation in real-time. The dependence of the viscoelastic properties of the network on strain rates and amplitudes as well as F-actin concentration is quantified. This approach provides the much-needed link between induced force and deformation over localized regimes (tens of microns) and down to the single molecule level.

  11. Induction of cell self-organization on weakly positively charged surfaces prepared by the deposition of polyion complex nanoparticles of thermoresponsive, zwitterionic copolymers.

    PubMed

    Iwai, Ryosuke; Haruki, Ryota; Nemoto, Yasushi; Nakayama, Yasuhide

    2017-07-01

    We have developed inducible cell self-organization through weakly positively charged culture surfaces. In this study, a thermoresponsive and zwitterionic copolymer comprised of N,N-dimethylaminoethyl methacrylate (DMAEMA) and methacrylic acid (MA) (PDMAEMA-co-PMA; Mn: ∼9.7 × 10 4 g/mol; PDMAEMA/PMA ratio: 10) was designed for inducing cell self-organization. The copolymer formed single polymer-derived polyion complex (sPIC) nanoparticles following dissolution in an aqueous solution. The sPIC nanoparticles had a positive charge (ca. 25 mV). Self-organization occurred in adipose-derived vascular stromal cell monolayers cultivated on sPIC-deposited surfaces. There were dramatic morphological changes of these cells with the formation of capillary-like networks and single-cell aggregates with little cytotoxicity. This was a significant improvement compared with cells grown on previously developed surfaces deposited with PIC, a mixture of PDMAEMA and plasmid DNA. Thus, sPICs of PDMAEMA-co-PMA may allow for the accurate evaluation of a variety of cell behaviors with less cytotoxicity, and may facilitate additional potential medical applications such as cell-based therapy and drug discovery. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 1009-1015, 2017. © 2016 Wiley Periodicals, Inc.

  12. Theoretical model for optical oximetry at the capillary level: exploring hemoglobin oxygen saturation through backscattering of single red blood cells

    NASA Astrophysics Data System (ADS)

    Liu, Rongrong; Spicer, Graham; Chen, Siyu; Zhang, Hao F.; Yi, Ji; Backman, Vadim

    2017-02-01

    Oxygen saturation (sO2) of red blood cells (RBCs) in capillaries can indirectly assess local tissue oxygenation and metabolic function. For example, the altered retinal oxygenation in diabetic retinopathy and local hypoxia during tumor development in cancer are reflected by abnormal sO2 of local capillary networks. However, it is far from clear whether accurate label-free optical oximetry (i.e., measuring hemoglobin sO2) is feasible from dispersed RBCs at the single capillary level. The sO2-dependent hemoglobin absorption contrast present in optical scattering signal is complicated by geometry-dependent scattering from RBCs. We present a numerical study of backscattering spectra from single RBCs based on the first-order Born approximation, considering practical factors: RBC orientations, size variation, and deformations. We show that the oscillatory spectral behavior of RBC geometries is smoothed by variations in cell size and orientation, resulting in clear sO2-dependent spectral contrast. In addition, this spectral contrast persists with different mean cellular hemoglobin content and different deformations of RBCs. This study shows for the first time the feasibility of, and provides a theoretical model for, label-free optical oximetry at the single capillary level using backscattering-based imaging modalities, challenging the popular view that such measurements are impossible at the single capillary level.

  13. Metastatic outgrowth encompasses COL-I, FN1, and POSTN up-regulation and assembly to fibrillar networks regulating cell adhesion, migration, and growth.

    PubMed

    Soikkeli, Johanna; Podlasz, Piotr; Yin, Miao; Nummela, Pirjo; Jahkola, Tiina; Virolainen, Susanna; Krogerus, Leena; Heikkilä, Päivi; von Smitten, Karl; Saksela, Olli; Hölttä, Erkki

    2010-07-01

    Although the outgrowth of micrometastases into macrometastases is the rate-limiting step in metastatic progression and the main determinant of cancer fatality, the molecular mechanisms involved have been little studied. Here, we compared the gene expression profiles of melanoma lymph node micro- and macrometastases and unexpectedly found no common up-regulation of any single growth factor/cytokine, except for the cytokine-like SPP1. Importantly, metastatic outgrowth was found to be consistently associated with activation of the transforming growth factor-beta signaling pathway (confirmed by phospho-SMAD2 staining) and concerted up-regulation of POSTN, FN1, COL-I, and VCAN genes-all inducible by transforming growth factor-beta. The encoded extracellular matrix proteins were found to together form intricate fibrillar networks around tumor cell nests in melanoma and breast cancer metastases from various organs. Functional analyses suggested that these newly synthesized protein networks regulate adhesion, migration, and growth of tumor cells, fibroblasts, and endothelial cells. POSTN acted as an anti-adhesive molecule counteracting the adhesive functions of FN1 and COL-I. Further, cellular FN and POSTN were specifically overexpressed in the newly forming/formed tumor blood vessels. Transforming growth factor-beta receptors and the metastasis-related matrix proteins, POSTN and FN1, in particular, may thus provide attractive targets for development of new therapies against disseminated melanoma, breast cancer, and possibly other tumors, by affecting key processes of metastasis: tumor/stromal cell migration, growth, and angiogenesis.

  14. Large-Scale Chemical Similarity Networks for Target Profiling of Compounds Identified in Cell-Based Chemical Screens

    PubMed Central

    Lo, Yu-Chen; Senese, Silvia; Li, Chien-Ming; Hu, Qiyang; Huang, Yong; Damoiseaux, Robert; Torres, Jorge Z.

    2015-01-01

    Target identification is one of the most critical steps following cell-based phenotypic chemical screens aimed at identifying compounds with potential uses in cell biology and for developing novel disease therapies. Current in silico target identification methods, including chemical similarity database searches, are limited to single or sequential ligand analysis that have limited capabilities for accurate deconvolution of a large number of compounds with diverse chemical structures. Here, we present CSNAP (Chemical Similarity Network Analysis Pulldown), a new computational target identification method that utilizes chemical similarity networks for large-scale chemotype (consensus chemical pattern) recognition and drug target profiling. Our benchmark study showed that CSNAP can achieve an overall higher accuracy (>80%) of target prediction with respect to representative chemotypes in large (>200) compound sets, in comparison to the SEA approach (60–70%). Additionally, CSNAP is capable of integrating with biological knowledge-based databases (Uniprot, GO) and high-throughput biology platforms (proteomic, genetic, etc) for system-wise drug target validation. To demonstrate the utility of the CSNAP approach, we combined CSNAP's target prediction with experimental ligand evaluation to identify the major mitotic targets of hit compounds from a cell-based chemical screen and we highlight novel compounds targeting microtubules, an important cancer therapeutic target. The CSNAP method is freely available and can be accessed from the CSNAP web server (http://services.mbi.ucla.edu/CSNAP/). PMID:25826798

  15. Neural signal registration and analysis of axons grown in microchannels

    NASA Astrophysics Data System (ADS)

    Pigareva, Y.; Malishev, E.; Gladkov, A.; Kolpakov, V.; Bukatin, A.; Mukhina, I.; Kazantsev, V.; Pimashkin, A.

    2016-08-01

    Registration of neuronal bioelectrical signals remains one of the main physical tools to study fundamental mechanisms of signal processing in the brain. Neurons generate spiking patterns which propagate through complex map of neural network connectivity. Extracellular recording of isolated axons grown in microchannels provides amplification of the signal for detailed study of spike propagation. In this study we used neuronal hippocampal cultures grown in microfluidic devices combined with microelectrode arrays to investigate a changes of electrical activity during neural network development. We found that after 5 days in vitro after culture plating the spiking activity appears first in microchannels and on the next 2-3 days appears on the electrodes of overall neural network. We conclude that such approach provides a convenient method to study neural signal processing and functional structure development on a single cell and network level of the neuronal culture.

  16. Relaxation rates of gene expression kinetics reveal the feedback signs of autoregulatory gene networks

    NASA Astrophysics Data System (ADS)

    Jia, Chen; Qian, Hong; Chen, Min; Zhang, Michael Q.

    2018-03-01

    The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression.

  17. Fitness landscape transformation through a single amino acid change in the rho terminator.

    PubMed

    Freddolino, Peter L; Goodarzi, Hani; Tavazoie, Saeed

    2012-05-01

    Regulatory networks allow organisms to match adaptive behavior to the complex and dynamic contingencies of their native habitats. Upon a sudden transition to a novel environment, the mismatch between the native behavior and the new niche provides selective pressure for adaptive evolution through mutations in elements that control gene expression. In the case of core components of cellular regulation and metabolism, with broad control over diverse biological processes, such mutations may have substantial pleiotropic consequences. Through extensive phenotypic analyses, we have characterized the systems-level consequences of one such mutation (rho*) in the global transcriptional terminator Rho of Escherichia coli. We find that a single amino acid change in Rho results in a massive change in the fitness landscape of the cell, with widely discrepant fitness consequences of identical single locus perturbations in rho* versus rho(WT) backgrounds. Our observations reveal the extent to which a single regulatory mutation can transform the entire fitness landscape of the cell, causing a massive change in the interpretation of individual mutations and altering the evolutionary trajectories which may be accessible to a bacterial population.

  18. A novel single-parameter approach for forecasting algal blooms.

    PubMed

    Xiao, Xi; He, Junyu; Huang, Haomin; Miller, Todd R; Christakos, George; Reichwaldt, Elke S; Ghadouani, Anas; Lin, Shengpan; Xu, Xinhua; Shi, Jiyan

    2017-01-01

    Harmful algal blooms frequently occur globally, and forecasting could constitute an essential proactive strategy for bloom control. To decrease the cost of aquatic environmental monitoring and increase the accuracy of bloom forecasting, a novel single-parameter approach combining wavelet analysis with artificial neural networks (WNN) was developed and verified based on daily online monitoring datasets of algal density in the Siling Reservoir, China and Lake Winnebago, U.S.A. Firstly, a detailed modeling process was illustrated using the forecasting of cyanobacterial cell density in the Chinese reservoir as an example. Three WNN models occupying various prediction time intervals were optimized through model training using an early stopped training approach. All models performed well in fitting historical data and predicting the dynamics of cyanobacterial cell density, with the best model predicting cyanobacteria density one-day ahead (r = 0.986 and mean absolute error = 0.103 × 10 4  cells mL -1 ). Secondly, the potential of this novel approach was further confirmed by the precise predictions of algal biomass dynamics measured as chl a in both study sites, demonstrating its high performance in forecasting algal blooms, including cyanobacteria as well as other blooming species. Thirdly, the WNN model was compared to current algal forecasting methods (i.e. artificial neural networks, autoregressive integrated moving average model), and was found to be more accurate. In addition, the application of this novel single-parameter approach is cost effective as it requires only a buoy-mounted fluorescent probe, which is merely a fraction (∼15%) of the cost of a typical auto-monitoring system. As such, the newly developed approach presents a promising and cost-effective tool for the future prediction and management of harmful algal blooms. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast

    PubMed Central

    Ye, Ping; Peyser, Brian D; Spencer, Forrest A; Bader, Joel S

    2005-01-01

    Background In a genetic interaction, the phenotype of a double mutant differs from the combined phenotypes of the underlying single mutants. When the single mutants have no growth defect, but the double mutant is lethal or exhibits slow growth, the interaction is termed synthetic lethality or synthetic fitness. These genetic interactions reveal gene redundancy and compensating pathways. Recently available large-scale data sets of genetic interactions and protein interactions in Saccharomyces cerevisiae provide a unique opportunity to elucidate the topological structure of biological pathways and how genes function in these pathways. Results We have defined congruent genes as pairs of genes with similar sets of genetic interaction partners and constructed a genetic congruence network by linking congruent genes. By comparing path lengths in three types of networks (genetic interaction, genetic congruence, and protein interaction), we discovered that high genetic congruence not only exhibits correlation with direct protein interaction linkage but also exhibits commensurate distance with the protein interaction network. However, consistent distances were not observed between genetic and protein interaction networks. We also demonstrated that congruence and protein networks are enriched with motifs that indicate network transitivity, while the genetic network has both transitive (triangle) and intransitive (square) types of motifs. These results suggest that robustness of yeast cells to gene deletions is due in part to two complementary pathways (square motif) or three complementary pathways, any two of which are required for viability (triangle motif). Conclusion Genetic congruence is superior to genetic interaction in prediction of protein interactions and function associations. Genetically interacting pairs usually belong to parallel compensatory pathways, which can generate transitive motifs (any two of three pathways needed) or intransitive motifs (either of two pathways needed). PMID:16283923

  20. Predictive lethal proarrhythmic risk evaluation using a closed-loop-circuit cell network with human induced pluripotent stem cells derived cardiomyocytes

    NASA Astrophysics Data System (ADS)

    Nomura, Fumimasa; Hattori, Akihiro; Terazono, Hideyuki; Kim, Hyonchol; Odaka, Masao; Sugio, Yoshihiro; Yasuda, Kenji

    2016-06-01

    For the prediction of lethal arrhythmia occurrence caused by abnormality of cell-to-cell conduction, we have developed a next-generation in vitro cell-to-cell conduction assay, i.e., a quasi in vivo assay, in which the change in spatial cell-to-cell conduction is quantitatively evaluated from the change in waveforms of the convoluted electrophysiological signals from lined-up cardiomyocytes on a single closed loop of a microelectrode of 1 mm diameter and 20 µm width in a cultivation chip. To evaluate the importance of the closed-loop arrangement of cardiomyocytes for prediction, we compared the change in waveforms of convoluted signals of the responses in the closed-loop circuit arrangement with that of the response of cardiomyocyte clusters using a typical human ether a go-go related gene (hERG) ion channel blocker, E-4031. The results showed that (1) waveform prolongation and fluctuation both in the closed loops and clusters increased depending on the E-4031 concentration increase. However, (2) only the waveform signals in closed loops showed an apparent temporal change in waveforms from ventricular tachycardia (VT) to ventricular fibrillation (VF), which is similar to the most typical cell-to-cell conductance abnormality. The results indicated the usefulness of convoluted waveform signals of a closed-loop cell network for acquiring reproducible results acquisition and more detailed temporal information on cell-to-cell conduction.

  1. Proton beam writing of microstructures in Agar gel for patterned cell growth

    NASA Astrophysics Data System (ADS)

    Larisch, Wolfgang; Koal, Torsten; Werner, Ronald; Hohlweg, Marcus; Reinert, Tilo; Butz, Tilman

    2011-10-01

    A rather useful prerequisite for many biological and biophysical studies, e.g., for cell-cell communication or neuronal networks, is confined cell growth on micro-structured surfaces. Solidified Agar layers have smooth surfaces which are electrically neutral and thus inhibit receptor binding and cell adhesion. For the first time, Agar microstructures have been manufactured using proton beam writing (PBW). In the irradiated Agar material the polysaccharides are split into oligosaccharides which can easily be washed off leaving Agar-free areas for cell adhesion. The beam diameter of 1 μm allows the fabrication of compartments accommodating single cells which are connected by micrometer-sized channels. Using the external beam the production process is very fast. Up to 50 Petri dishes can be produced per day which makes this technique very suitable for biological investigations which require large throughputs.

  2. Practical approximation method for firing-rate models of coupled neural networks with correlated inputs

    NASA Astrophysics Data System (ADS)

    Barreiro, Andrea K.; Ly, Cheng

    2017-08-01

    Rapid experimental advances now enable simultaneous electrophysiological recording of neural activity at single-cell resolution across large regions of the nervous system. Models of this neural network activity will necessarily increase in size and complexity, thus increasing the computational cost of simulating them and the challenge of analyzing them. Here we present a method to approximate the activity and firing statistics of a general firing rate network model (of the Wilson-Cowan type) subject to noisy correlated background inputs. The method requires solving a system of transcendental equations and is fast compared to Monte Carlo simulations of coupled stochastic differential equations. We implement the method with several examples of coupled neural networks and show that the results are quantitatively accurate even with moderate coupling strengths and an appreciable amount of heterogeneity in many parameters. This work should be useful for investigating how various neural attributes qualitatively affect the spiking statistics of coupled neural networks.

  3. Determining geophysical properties from well log data using artificial neural networks and fuzzy inference systems

    NASA Astrophysics Data System (ADS)

    Chang, Hsien-Cheng

    Two novel synergistic systems consisting of artificial neural networks and fuzzy inference systems are developed to determine geophysical properties by using well log data. These systems are employed to improve the determination accuracy in carbonate rocks, which are generally more complex than siliciclastic rocks. One system, consisting of a single adaptive resonance theory (ART) neural network and three fuzzy inference systems (FISs), is used to determine the permeability category. The other system, which is composed of three ART neural networks and a single FIS, is employed to determine the lithofacies. The geophysical properties studied in this research, permeability category and lithofacies, are treated as categorical data. The permeability values are transformed into a "permeability category" to account for the effects of scale differences between core analyses and well logs, and heterogeneity in the carbonate rocks. The ART neural networks dynamically cluster the input data sets into different groups. The FIS is used to incorporate geologic experts' knowledge, which is usually in linguistic forms, into systems. These synergistic systems thus provide viable alternative solutions to overcome the effects of heterogeneity, the uncertainties of carbonate rock depositional environments, and the scarcity of well log data. The results obtained in this research show promising improvements over backpropagation neural networks. For the permeability category, the prediction accuracies are 68.4% and 62.8% for the multiple-single ART neural network-FIS and a single backpropagation neural network, respectively. For lithofacies, the prediction accuracies are 87.6%, 79%, and 62.8% for the single-multiple ART neural network-FIS, a single ART neural network, and a single backpropagation neural network, respectively. The sensitivity analysis results show that the multiple-single ART neural networks-FIS and a single ART neural network possess the same matching trends in determining lithofacies. This research shows that the adaptive resonance theory neural networks enable decision-makers to clearly distinguish the importance of different pieces of data which are useful in three-dimensional subsurface modeling. Geologic experts' knowledge can be easily applied and maintained by using the fuzzy inference systems.

  4. Photothermally triggered actuation of hybrid materials as a new platform for in vitro cell manipulation

    NASA Astrophysics Data System (ADS)

    Sutton, Amy; Shirman, Tanya; Timonen, Jaakko V. I.; England, Grant T.; Kim, Philseok; Kolle, Mathias; Ferrante, Thomas; Zarzar, Lauren D.; Strong, Elizabeth; Aizenberg, Joanna

    2017-03-01

    Mechanical forces in the cell's natural environment have a crucial impact on growth, differentiation and behaviour. Few areas of biology can be understood without taking into account how both individual cells and cell networks sense and transduce physical stresses. However, the field is currently held back by the limitations of the available methods to apply physiologically relevant stress profiles on cells, particularly with sub-cellular resolution, in controlled in vitro experiments. Here we report a new type of active cell culture material that allows highly localized, directional and reversible deformation of the cell growth substrate, with control at scales ranging from the entire surface to the subcellular, and response times on the order of seconds. These capabilities are not matched by any other method, and this versatile material has the potential to bridge the performance gap between the existing single cell micro-manipulation and 2D cell sheet mechanical stimulation techniques.

  5. Integrating Metal-Oxide-Decorated CNT Networks with a CMOS Readout in a Gas Sensor

    PubMed Central

    Lee, Hyunjoong; Lee, Sanghoon; Kim, Dai-Hong; Perello, David; Park, Young June; Hong, Seong-Hyeon; Yun, Minhee; Kim, Suhwan

    2012-01-01

    We have implemented a tin-oxide-decorated carbon nanotube (CNT) network gas sensor system on a single die. We have also demonstrated the deposition of metallic tin on the CNT network, its subsequent oxidation in air, and the improvement of the lifetime of the sensors. The fabricated array of CNT sensors contains 128 sensor cells for added redundancy and increased accuracy. The read-out integrated circuit (ROIC) was combined with coarse and fine time-to-digital converters to extend its resolution in a power-efficient way. The ROIC is fabricated using a 0.35 μm CMOS process, and the whole sensor system consumes 30 mA at 5 V. The sensor system was successfully tested in the detection of ammonia gas at elevated temperatures. PMID:22736966

  6. Modeling microcirculatory blood flow: current state and future perspectives.

    PubMed

    Gompper, Gerhard; Fedosov, Dmitry A

    2016-01-01

    Microvascular blood flow determines a number of important physiological processes of an organism in health and disease. Therefore, a detailed understanding of microvascular blood flow would significantly advance biophysical and biomedical research and its applications. Current developments in modeling of microcirculatory blood flow already allow to go beyond available experimental measurements and have a large potential to elucidate blood flow behavior in normal and diseased microvascular networks. There exist detailed models of blood flow on a single cell level as well as simplified models of the flow through microcirculatory networks, which are reviewed and discussed here. The combination of these models provides promising prospects for better understanding of blood flow behavior and transport properties locally as well as globally within large microvascular networks. © 2015 Wiley Periodicals, Inc.

  7. A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells

    PubMed Central

    2012-01-01

    Background CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions. Results We present a simple theoretical framework to show how heterogeneous differentiation in a two-master-regulator paradigm can be governed by a signaling network motif common to all subsets of CD4+ T cells. With this motif, a population of naïve CD4+ T cells can integrate the signals from their environment to generate a functionally diverse population with robust commitment of individual cells. Notably, two positive feedback loops in this network motif govern three bistable switches, which in turn, give rise to three types of heterogeneous differentiated states, depending upon particular combinations of input signals. We provide three prototype models illustrating how to use this framework to explain experimental observations and make specific testable predictions. Conclusions The process in which several types of T helper cells are generated simultaneously to mount complex immune responses upon pathogenic challenges can be highly regulated, and a simple signaling network motif can be responsible for generating all possible types of heterogeneous populations with respect to a pair of master regulators controlling CD4+ T cell differentiation. The framework provides a mathematical basis for understanding the decision-making mechanisms of CD4+ T cells, and it can be helpful for interpreting experimental results. Mathematical models based on the framework make specific testable predictions that may improve our understanding of this differentiation system. PMID:22697466

  8. Method and apparatus for pulse stacking

    DOEpatents

    Harney, Robert C.

    1977-01-01

    An active pulse stacking system including an etalon and an electro-optical modulator apparatus combined with a pulse-forming network capable of forming and summing a sequence of time-delayed optical waveforms arising from, for example, a single laser pulse. The Pockels cell pulse stacker may attain an efficiency of about 2.6% while providing a controllable faster-than-exponential time rise in transmitted pulse intensity.

  9. Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer.

    PubMed

    Gao, Xue-Xin; Gao, Lei; Wang, Jiu-Qiang; Qu, Su-Su; Qu, Yue; Sun, Hong-Lei; Liu, Si-Dang; Shang, Ying-Li

    2016-07-12

    Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce.In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis.Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC.Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC.

  10. Reflection-mode micro-spherical fiber-optic probes for in vitro real-time and single-cell level pH sensing.

    PubMed

    Yang, Qingbo; Wang, Hanzheng; Lan, Xinwei; Cheng, Baokai; Chen, Sisi; Shi, Honglan; Xiao, Hai; Ma, Yinfa

    2015-02-01

    pH sensing at the single-cell level without negatively affecting living cells is very important but still a remaining issue in the biomedical studies. A 70 μm reflection-mode fiber-optic micro-pH sensor was designed and fabricated by dip-coating thin layer of organically modified aerogel onto a tapered spherical probe head. A pH sensitive fluorescent dye 2', 7'-Bis (2-carbonylethyl)-5(6)-carboxyfluorescein (BCECF) was employed and covalently bonded within the aerogel networks. By tuning the alkoxide mixing ratio and adjusting hexamethyldisilazane (HMDS) priming procedure, the sensor can be optimized to have high stability and pH sensing ability. The in vitro real-time sensing capability was then demonstrated in a simple spectroscopic way, and showed linear measurement responses with a pH resolution up to an average of 0.049 pH unit within a narrow, but biological meaningful pH range of 6.12-7.81. Its novel characterizations of high spatial resolution, reflection mode operation, fast response and high stability, great linear response within biological meaningful pH range and high pH resolutions, make this novel pH probe a very cost-effective tool for chemical/biological sensing, especially within the single cell level research field.

  11. Intersection of FOXO- and RUNX1-mediated gene expression programs in single breast epithelial cells during morphogenesis and tumor progression.

    PubMed

    Wang, Lixin; Brugge, Joan S; Janes, Kevin A

    2011-10-04

    Gene expression networks are complicated by the assortment of regulatory factors that bind DNA and modulate transcription combinatorially. Single-cell measurements can reveal biological mechanisms hidden by population averages, but their value has not been fully explored in the context of mRNA regulation. Here, we adapted a single-cell expression profiling technique to examine the gene expression program downstream of Forkhead box O (FOXO) transcription factors during 3D breast epithelial acinar morphogenesis. By analyzing patterns of mRNA fluctuations among individual matrix-attached epithelial cells, we found that a subset of FOXO target genes was jointly regulated by the transcription factor Runt-related transcription factor 1 (RUNX1). Knockdown of RUNX1 causes hyperproliferation and abnormal morphogenesis, both of which require normal FOXO function. Down-regulating RUNX1 and FOXOs simultaneously causes widespread oxidative stress, which arrests proliferation and restores normal acinar morphology. In hormone-negative breast cancers lacking human epidermal growth factor receptor 2 (HER2) amplification, we find that RUNX1 down-regulation is strongly associated with up-regulation of FOXO1, which may be required to support growth of RUNX1-negative tumors. The coordinate function of these two tumor suppressors may provide a failsafe mechanism that inhibits cancer progression.

  12. Reflection-mode micro-spherical fiber-optic probes for in vitro real-time and single-cell level pH sensing

    PubMed Central

    Yang, Qingbo; Wang, Hanzheng; Lan, Xinwei; Cheng, Baokai; Chen, Sisi; Shi, Honglan; Xiao, Hai; Ma, Yinfa

    2014-01-01

    pH sensing at the single-cell level without negatively affecting living cells is very important but still a remaining issue in the biomedical studies. A 70 μm reflection-mode fiber-optic micro-pH sensor was designed and fabricated by dip-coating thin layer of organically modified aerogel onto a tapered spherical probe head. A pH sensitive fluorescent dye 2′, 7′-Bis (2-carbonylethyl)-5(6)-carboxyfluorescein (BCECF) was employed and covalently bonded within the aerogel networks. By tuning the alkoxide mixing ratio and adjusting hexamethyldisilazane (HMDS) priming procedure, the sensor can be optimized to have high stability and pH sensing ability. The in vitro real-time sensing capability was then demonstrated in a simple spectroscopic way, and showed linear measurement responses with a pH resolution up to an average of 0.049 pH unit within a narrow, but biological meaningful pH range of 6.12–7.81. Its novel characterizations of high spatial resolution, reflection mode operation, fast response and high stability, great linear response within biological meaningful pH range and high pH resolutions, make this novel pH probe a very cost-effective tool for chemical/biological sensing, especially within the single cell level research field. PMID:25530670

  13. Modelling biofilm-induced formation damage and biocide treatment in subsurface geosystems

    PubMed Central

    Ezeuko, C C; Sen, A; Gates, I D

    2013-01-01

    Biofilm growth in subsurface porous media, and its treatment with biocides (antimicrobial agents), involves a complex interaction of biogeochemical processes which provide non-trivial mathematical modelling challenges. Although there are literature reports of mathematical models to evaluate biofilm tolerance to biocides, none of these models have investigated biocide treatment of biofilms growing in interconnected porous media with flow. In this paper, we present a numerical investigation using a pore network model of biofilm growth, formation damage and biocide treatment. The model includes three phases (aqueous, adsorbed biofilm, and solid matrix), a single growth-limiting nutrient and a single biocide dissolved in the water. Biofilm is assumed to contain a single species of microbe, in which each cell can be a viable persister, a viable non-persister, or non-viable (dead). Persisters describe small subpopulation of cells which are tolerant to biocide treatment. Biofilm tolerance to biocide treatment is regulated by persister cells and includes ‘innate’ and ‘biocide-induced’ factors. Simulations demonstrate that biofilm tolerance to biocides can increase with biofilm maturity, and that biocide treatment alone does not reverse biofilm-induced formation damage. Also, a successful application of biological permeability conformance treatment involving geologic layers with flow communication is more complicated than simply engineering the attachment of biofilm-forming cells at desired sites. PMID:23164434

  14. Comparative analysis of single-cell RNA sequencing data from mouse spermatogonial and mesenchymal stem cells to identify differentially expressed genes and transcriptional regulators of germline cells.

    PubMed

    Sisakhtnezhad, Sajjad; Heshmati, Parvin

    2018-07-01

    Identifying effective internal factors for regulating germline commitment during development and for maintaining spermatogonial stem cells (SSCs) self-renewal is important to understand the molecular basis of spermatogenesis process, and to develop new protocols for the production of the germline cells from other cell sources. Therefore, this study was designed to investigate single-cell RNA-sequencing data for identification of differentially expressed genes (DEGs) in 12 mouse-derived single SSCs (mSSCs) in compare with 16 mouse-derived single mesenchymal stem cells. We also aimed to find transcriptional regulators of DEGs. Collectively, 1,584 up-regulated DEGs were identified that are associated with 32 biological processes. Moreover, investigation of the expression profiles of genes including in spermatogenesis process revealed that Dazl, Ddx4, Sall4, Fkbp6, Tex15, Tex19.1, Rnf17, Piwil2, Taf7l, Zbtb16, and Cadm1 are presented in the first 30 up-regulated DEGs. We also found 12 basal transcription factors (TFs) and three sequence-specific TFs that control the expression of DEGs. Our findings also indicated that MEIS1, SMC3, TAF1, KAT2A, STAT3, GTF3C2, SIN3A, BDP1, PHC1, and EGR1 are the main central regulators of DEGs in mSSCs. In addition, we collectively detected two significant protein complexes in the protein-protein interactions network for DEGs regulators. Finally, this study introduces the major upstream kinases for the main central regulators of DEGs and the components of core protein complexes. In conclusion, this study provides a molecular blueprint to uncover the molecular mechanisms behind the biology of SSCs and offers a list of candidate factors for cell type conversion approaches and production of germ cells. © 2017 Wiley Periodicals, Inc.

  15. An optofluidic channel model for in vivo nanosensor networks in human blood

    NASA Astrophysics Data System (ADS)

    Johari, Pedram; Jornet, Josep M.

    2017-05-01

    In vivo Wireless Nanosensor Networks (iWNSNs) consist of nano-sized communicating devices with unprece- dented sensing and actuation capabilities, which are able to operate inside the human body. iWNSNs are a disruptive technology that enables the monitoring and control of biological processes at the cellular and sub- cellular levels. Compared to ex vivo measurements, which are conducted on samples extracted from the human body, iWNSNs can track (sub) cellular processes when and where they occur. Major progress in the field of na- noelectronics, nanophotonics and wireless communication is enabling the interconnection of nanosensors. Among others, plasmonic nanolasers with sub-micrometric footprint, plasmonic nano-antennas able to confine light in nanometric structures, and single-photon detectors with unrivaled sensitivity, enable the communication among implanted nanosensors in the near infrared and optical transmission windows. Motivated by these results, in this paper, an optofluidic channel model is developed to investigate the communication properties and temporal dynamics between a pair of in vivo nanosensors in the human blood. The developed model builds upon the authors' recent work on light propagation modeling through multi-layered single cells and cell assemblies and takes into account the geometric, electromagnetic and microfluidic properties of red blood cells in the human circulatory system. The proposed model guides the development of practical communication strategies among nanosensors, and paves the way through new nano-biosensing strategies able to identify diseases by detecting the slight changes in the channel impulse response, caused by either the change in shape of the blood cells or the presence of pathogens.

  16. Understanding genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Kauffman, Stuart

    2003-04-01

    Random Boolean networks (RBM) were introduced about 35 years ago as first crude models of genetic regulatory networks. RBNs are comprised of N on-off genes, connected by a randomly assigned regulatory wiring diagram where each gene has K inputs, and each gene is controlled by a randomly assigned Boolean function. This procedure samples at random from the ensemble of all possible NK Boolean networks. The central ideas are to study the typical, or generic properties of this ensemble, and see 1) whether characteristic differences appear as K and biases in Boolean functions are introducted, and 2) whether a subclass of this ensemble has properties matching real cells. Such networks behave in an ordered or a chaotic regime, with a phase transition, "the edge of chaos" between the two regimes. Networks with continuous variables exhibit the same two regimes. Substantial evidence suggests that real cells are in the ordered regime. A key concept is that of an attractor. This is a reentrant trajectory of states of the network, called a state cycle. The central biological interpretation is that cell types are attractors. A number of properties differentiate the ordered and chaotic regimes. These include the size and number of attractors, the existence in the ordered regime of a percolating "sea" of genes frozen in the on or off state, with a remainder of isolated twinkling islands of genes, a power law distribution of avalanches of gene activity changes following perturbation to a single gene in the ordered regime versus a similar power law distribution plus a spike of enormous avalanches of gene changes in the chaotic regime, and the existence of branching pathway of "differentiation" between attractors induced by perturbations in the ordered regime. Noise is serious issue, since noise disrupts attractors. But numerical evidence suggests that attractors can be made very stable to noise, and meanwhile, metaplasias may be a biological manifestation of noise. As we learn more about the wiring diagram and constraints on rules controlling real genes, we can build refined ensembles reflecting these properties, study the generic properties of the refined ensembles, and hope to gain insight into the dynamics of real cells.

  17. Network design and analysis for multi-enzyme biocatalysis.

    PubMed

    Blaß, Lisa Katharina; Weyler, Christian; Heinzle, Elmar

    2017-08-10

    As more and more biological reaction data become available, the full exploration of the enzymatic potential for the synthesis of valuable products opens up exciting new opportunities but is becoming increasingly complex. The manual design of multi-step biosynthesis routes involving enzymes from different organisms is very challenging. To harness the full enzymatic potential, we developed a computational tool for the directed design of biosynthetic production pathways for multi-step catalysis with in vitro enzyme cascades, cell hydrolysates and permeabilized cells. We present a method which encompasses the reconstruction of a genome-scale pan-organism metabolic network, path-finding and the ranking of the resulting pathway candidates for proposing suitable synthesis pathways. The network is based on reaction and reaction pair data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the thermodynamics calculator eQuilibrator. The pan-organism network is especially useful for finding the most suitable pathway to a target metabolite from a thermodynamic or economic standpoint. However, our method can be used with any network reconstruction, e.g. for a specific organism. We implemented a path-finding algorithm based on a mixed-integer linear program (MILP) which takes into account both topology and stoichiometry of the underlying network. Unlike other methods we do not specify a single starting metabolite, but our algorithm searches for pathways starting from arbitrary start metabolites to a target product of interest. Using a set of biochemical ranking criteria including pathway length, thermodynamics and other biological characteristics such as number of heterologous enzymes or cofactor requirement, it is possible to obtain well-designed meaningful pathway alternatives. In addition, a thermodynamic profile, the overall reactant balance and potential side reactions as well as an SBML file for visualization are generated for each pathway alternative. We present an in silico tool for the design of multi-enzyme biosynthetic production pathways starting from a pan-organism network. The method is highly customizable and each module can be adapted to the focus of the project at hand. This method is directly applicable for (i) in vitro enzyme cascades, (ii) cell hydrolysates and (iii) permeabilized cells.

  18. Nuclear traffic and peloton formation in fungal networks

    NASA Astrophysics Data System (ADS)

    Roper, Marcus; Hickey, Patrick; Lewkiewicz, Stephanie; Dressaire, Emilie; Read, Nick

    2013-11-01

    Hyphae, the network of microfluidic pipes that make up a growing fungal cell, must balance their function as conduits for the transport of nuclei with other cellular functions including secretion and growth. Constant flow of nuclei may interfere with the protein traffic that enables other functions to be performed. Live-cell imaging reveals that nuclear flows are anti-congestive; that groups of nuclei flow faster than single nuclei, and that nuclei sweep through the colony in dense clumps. We call these clumps pelotons, after the term used to describe groups of cycle racers slip-streaming off each other. Because of the pelotons, individual hyphae transport nuclei only intermittently, producing long intervals in which hyphae can perform their other functions. Modeling reveals how pelotons are created by interactions between nuclei and the hyphal cytoskeleton, and reveal the control that the fungus enjoys over peloton assembly and timing.

  19. Atomic force microscopy based nanoindentation study of onion abaxial epidermis walls in aqueous environment

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

    Xi, Xiaoning; Tittmann, Bernhard; Kim, Seong H.

    An atomic force microscopy based nanoindentation method was employed to study how the structure of cellulose microfibril packing and matrix polymers affect elastic modulus of fully hydrated primary plant cell walls. The isolated, single-layered abaxial epidermis cell wall of an onion bulb was used as a test system since the cellulose microfibril packing in this cell wall is known to vary systematically from inside to outside scales and the most abundant matrix polymer, pectin, can easily be altered through simple chemical treatments such as ethylenediaminetetraacetic acid and calcium ions. Experimental results showed that the pectin network variation has significant impactsmore » on the cell wall modulus, and not the cellulose microfibril packing.« less

  20. The S(c)ensory Immune System Theory.

    PubMed

    Veiga-Fernandes, Henrique; Freitas, António A

    2017-10-01

    Viewpoints on the immune system have evolved across different paradigms, including the clonal selection theory, the idiotypic network, and the danger and tolerance models. Herein, we propose that in multicellular organisms, where panoplies of cells from different germ layers interact and immune cells are constantly generated, the behavior of the immune system is defined by the rules governing cell survival, systems physiology and organismic homeostasis. Initially, these rules were imprinted at the single cell-protist level, but supervened modifications in the transition to multicellular organisms. This context determined the emergence of the 'sensory immune system', which operates in a s(c)ensor mode to ensure systems physiology, organismic homeostasis, and perpetuation of its replicating molecules. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. A supramolecular gel electrolyte formed from amide based co-gelator for quasi-solid-state dye-sensitized solar cell with boosted electron kinetic processes

    NASA Astrophysics Data System (ADS)

    Huo, Zhipeng; Wang, Lu; Tao, Li; Ding, Yong; Yi, Jinxin; Alsaedi, Ahmed; Hayat, Tasawar; Dai, Songyuan

    2017-08-01

    A supramolecular gel electrolyte (Tgel > 100 °C) is formed from N,N‧-1,8-octanediylbis-dodecanamide and iodoacetamide as two-component co-gelator, and introduced into the quasi-solid-state dye-sensitized solar cells (QS-DSSCs). The different morphologies of microscopic network between two-component and single-component gel electrolytes have influence on the diffusion of redox couple in gel electrolytes and further affect the electron kinetic processes in QS-DSSCs. Compared with the single-component gel electrolyte, the two-component gel electrolyte has less compact gel network and weaker steric hindrance effect, which provides more effective charge transport channel for the diffusion of I3/I- redox couple. Meanwhile, the sbnd NH2 groups of iodoacetamide molecules interact with Li+ and I3-, which also accelerate the transport of I3-/I- and decrease in the I3- concentration in the TiO2/electrolyte interface. As a result, nearly a 12% improvement in short-circuit photocurrent density (Jsc) and much higher open circuit potential (Voc) are found in the two-component gel electrolyte based QS-DSSC. Consequently, the QS-DSSC based on the supramolecular gel electrolyte obtains a 17% enhancement in the photoelectric conversion efficiency (7.32%) in comparison with the QS-DSSC based on the single-component gel electrolyte (6.24%). Furthermore, the degradations of these QS-DSSCs are negligible after one sun light soaking with UV cutoff filter at 50 °C for 1000 h.

  2. Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms

    PubMed Central

    S, Shiju

    2017-01-01

    Molecular mechanisms responsible for 24 h circadian oscillations, entrainment to external cues, encoding of day length and the time-of-day effects have been well studied experimentally. However, it is still debated from the molecular network point of view whether each cell in suprachiasmatic nuclei harbors two molecular oscillators, where one tracks dawn and the other tracks dusk activities. A single cell dual morning and evening oscillator was proposed by Daan et al., based on the molecular network that has two sets of similar non-redundant per1/cry1 and per2/cry2 circadian genes and each can independently maintain their endogenous oscillations. Understanding of dual oscillator dynamics in a single cell at molecular level may provide insight about the circadian mechanisms that encodes day length variations and its response to external zeitgebers. We present here a realistic dual oscillator model of circadian rhythms based on the series of hypotheses proposed by Daan et al., in which they conjectured that the circadian genes per1/cry1 track dawn while per2/cry2 tracks dusk and they together constitute the morning and evening oscillators (dual oscillator). Their hypothesis also provides explanations about the encoding of day length in terms of molecular mechanisms of per/cry expression. We frame a minimal mathematical model with the assumption that per1 acts a morning oscillator and per2 acts as an evening oscillator and to support and interpret this assumption we fit the model to the experimental data of per1/per2 circadian temporal dynamics, phase response curves (PRC's), and entrainment phenomena under various light-dark conditions. We also capture different patterns of splitting phenomena by coupling two single cell dual oscillators with neuropeptides vasoactive intestinal polypeptide (VIP) and arginine vasopressin (AVP) as the coupling agents and provide interpretation for the occurrence of splitting in terms of ME oscillators, though they are not required to explain the morning and evening oscillators. The proposed dual oscillator model based on Daan's hypothesis supports per1 and per2 playing the role of morning and evening oscillators respectively and this may be the first step towards the understanding of the core molecular mechanism responsible for encoding the day length. PMID:28486525

  3. Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms.

    PubMed

    S, Shiju; Sriram, K

    2017-01-01

    Molecular mechanisms responsible for 24 h circadian oscillations, entrainment to external cues, encoding of day length and the time-of-day effects have been well studied experimentally. However, it is still debated from the molecular network point of view whether each cell in suprachiasmatic nuclei harbors two molecular oscillators, where one tracks dawn and the other tracks dusk activities. A single cell dual morning and evening oscillator was proposed by Daan et al., based on the molecular network that has two sets of similar non-redundant per1/cry1 and per2/cry2 circadian genes and each can independently maintain their endogenous oscillations. Understanding of dual oscillator dynamics in a single cell at molecular level may provide insight about the circadian mechanisms that encodes day length variations and its response to external zeitgebers. We present here a realistic dual oscillator model of circadian rhythms based on the series of hypotheses proposed by Daan et al., in which they conjectured that the circadian genes per1/cry1 track dawn while per2/cry2 tracks dusk and they together constitute the morning and evening oscillators (dual oscillator). Their hypothesis also provides explanations about the encoding of day length in terms of molecular mechanisms of per/cry expression. We frame a minimal mathematical model with the assumption that per1 acts a morning oscillator and per2 acts as an evening oscillator and to support and interpret this assumption we fit the model to the experimental data of per1/per2 circadian temporal dynamics, phase response curves (PRC's), and entrainment phenomena under various light-dark conditions. We also capture different patterns of splitting phenomena by coupling two single cell dual oscillators with neuropeptides vasoactive intestinal polypeptide (VIP) and arginine vasopressin (AVP) as the coupling agents and provide interpretation for the occurrence of splitting in terms of ME oscillators, though they are not required to explain the morning and evening oscillators. The proposed dual oscillator model based on Daan's hypothesis supports per1 and per2 playing the role of morning and evening oscillators respectively and this may be the first step towards the understanding of the core molecular mechanism responsible for encoding the day length.

  4. How Nucleus Mechanics and ECM Microstructure Influence the Invasion of Single Cells and Multicellular Aggregates.

    PubMed

    Giverso, Chiara; Arduino, Alessandro; Preziosi, Luigi

    2018-05-01

    In order to move in a three-dimensional extracellular matrix, the nucleus of a cell must squeeze through the narrow spacing among the fibers and, by adhering to them, the cell needs to exert sufficiently strong traction forces. If the nucleus is too stiff, the spacing too narrow, or traction forces too weak, the cell is not able to penetrate the network. In this article, we formulate a mathematical model based on an energetic approach, for cells entering cylindrical channels composed of extracellular matrix fibers. Treating the nucleus as an elastic body covered by an elastic membrane, the energetic balance leads to the definition of a necessary criterion for cells to pass through the regular network of fibers, depending on the traction forces exerted by the cells (or possibly passive stresses), the stretchability of the nuclear membrane, the stiffness of the nucleus, and the ratio of the pore size within the extracellular matrix with respect to the nucleus diameter. The results obtained highlight the importance of the interplay between mechanical properties of the cell and microscopic geometric characteristics of the extracellular matrix and give an estimate for a critical value of the pore size that represents the physical limit of migration and can be used in tumor growth models to predict their invasive potential in thick regions of ECM.

  5. Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation.

    PubMed

    Zhyvoloup, Alexander; Melamed, Anat; Anderson, Ian; Planas, Delphine; Lee, Chen-Hsuin; Kriston-Vizi, Janos; Ketteler, Robin; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R M; Fassati, Ariberto

    2017-07-01

    HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation.

  6. Dual Cross-Linked Biofunctional and Self-Healing Networks to Generate User-Defined Modular Gradient Hydrogel Constructs.

    PubMed

    Wei, Zhao; Lewis, Daniel M; Xu, Yu; Gerecht, Sharon

    2017-08-01

    Gradient hydrogels have been developed to mimic the spatiotemporal differences of multiple gradient cues in tissues. Current approaches used to generate such hydrogels are restricted to a single gradient shape and distribution. Here, a hydrogel is designed that includes two chemical cross-linking networks, biofunctional, and self-healing networks, enabling the customizable formation of modular gradient hydrogel construct with various gradient distributions and flexible shapes. The biofunctional networks are formed via Michael addition between the acrylates of oxidized acrylated hyaluronic acid (OAHA) and the dithiol of matrix metalloproteinase (MMP)-sensitive cross-linker and RGD peptides. The self-healing networks are formed via dynamic Schiff base reaction between N-carboxyethyl chitosan (CEC) and OAHA, which drives the modular gradient units to self-heal into an integral modular gradient hydrogel. The CEC-OAHA-MMP hydrogel exhibits excellent flowability at 37 °C under shear stress, enabling its injection to generate gradient distributions and shapes. Furthermore, encapsulated sarcoma cells respond to the gradient cues of RGD peptides and MMP-sensitive cross-linkers in the hydrogel. With these superior properties, the dual cross-linked CEC-OAHA-MMP hydrogel holds significant potential for generating customizable gradient hydrogel constructs, to study and guide cellular responses to their microenvironment such as in tumor mimicking, tissue engineering, and stem cell differentiation and morphogenesis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Proteolytic crosstalk in multi-protease networks

    NASA Astrophysics Data System (ADS)

    Ogle, Curtis T.; Mather, William H.

    2016-04-01

    Processive proteases, such as ClpXP in E. coli, are conserved enzyme assemblies that can recognize and rapidly degrade proteins. These proteases are used for a number of purposes, including degrading mistranslated proteins and controlling cellular stress response. However, proteolytic machinery within the cell is limited in capacity and can lead to a bottleneck in protein degradation, whereby many proteins compete (‘queue’) for proteolytic resources. Previous work has demonstrated that such queueing can lead to pronounced statistical relationships between different protein counts when proteins compete for a single common protease. However, real cells contain many different proteases, e.g. ClpXP, ClpAP, and Lon in E. coli, and it is not clear how competition between proteins for multiple classes of protease would influence the dynamics of cellular networks. In the present work, we theoretically demonstrate that a multi-protease proteolytic bottleneck can substantially couple the dynamics for both simple and complex (oscillatory) networks, even between substrates with substantially different affinities for protease. For these networks, queueing often leads to strong positive correlations between protein counts, and these correlations are strongest near the queueing theoretic point of balance. Furthermore, we find that the qualitative behavior of these networks depends on the relative size of the absolute affinity of substrate to protease compared to the cross affinity of substrate to protease, leading in certain regimes to priority queue statistics.

  8. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

    PubMed

    Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

    2017-04-01

    Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

  9. How cells explore shape space: a quantitative statistical perspective of cellular morphogenesis.

    PubMed

    Yin, Zheng; Sailem, Heba; Sero, Julia; Ardy, Rico; Wong, Stephen T C; Bakal, Chris

    2014-12-01

    Through statistical analysis of datasets describing single cell shape following systematic gene depletion, we have found that the morphological landscapes explored by cells are composed of a small number of attractor states. We propose that the topology of these landscapes is in large part determined by cell-intrinsic factors, such as biophysical constraints on cytoskeletal organization, and reflects different stable signaling and/or transcriptional states. Cell-extrinsic factors act to determine how cells explore these landscapes, and the topology of the landscapes themselves. Informational stimuli primarily drive transitions between stable states by engaging signaling networks, while mechanical stimuli tune, or even radically alter, the topology of these landscapes. As environments fluctuate, the topology of morphological landscapes explored by cells dynamically adapts to these fluctuations. Finally we hypothesize how complex cellular and tissue morphologies can be generated from a limited number of simple cell shapes. © 2014 WILEY Periodicals, Inc.

  10. a Mini Multi-Gas Detection System Based on Infrared Principle

    NASA Astrophysics Data System (ADS)

    Zhijian, Xie; Qiulin, Tan

    2006-12-01

    To counter the problems of gas accidents in coal mines, family safety resulted from using gas, a new infrared detection system with integration and miniaturization has been developed. The infrared detection optics principle used in developing this system is mainly analyzed. The idea that multi gas detection is introduced and guided through analyzing single gas detection is got across. Through researching the design of cell structure, the cell with integration and miniaturization has been devised. The way of data transmission on Controller Area Network (CAN) bus is explained. By taking Single-Chip Microcomputer (SCM) as intelligence handling, the functional block diagram of gas detection system is designed with its hardware and software system analyzed and devised. This system designed has reached the technology requirement of lower power consumption, mini-volume, big measure range, and able to realize multi-gas detection.

  11. Structures with three dimensional nanofences comprising single crystal segments

    DOEpatents

    Goyal, Amit; Wee, Sung-Hun

    2013-08-27

    An article includes a substrate having a surface and a nanofence supported by the surface. The nanofence includes a multiplicity of primary nanorods and branch nanorods, each of the primary nanorods being attached to said substrate, and each of the branch nanorods being attached to a primary nanorods and/or another branch nanorod. The primary and branch nanorods are arranged in a three-dimensional, interconnected, interpenetrating, grid-like network defining interstices within the nanofence. The article further includes an enveloping layer supported by the nanofence, disposed in the interstices, and forming a coating on the primary and branch nanorods. The enveloping layer has a different composition from that of the nanofence and includes a radial p-n single junction solar cell photovoltaic material and/or a radial p-n multiple junction solar cell photovoltaic material.

  12. The founding charter of the Genomic Observatories Network.

    PubMed

    Davies, Neil; Field, Dawn; Amaral-Zettler, Linda; Clark, Melody S; Deck, John; Drummond, Alexei; Faith, Daniel P; Geller, Jonathan; Gilbert, Jack; Glöckner, Frank Oliver; Hirsch, Penny R; Leong, Jo-Ann; Meyer, Chris; Obst, Matthias; Planes, Serge; Scholin, Chris; Vogler, Alfried P; Gates, Ruth D; Toonen, Rob; Berteaux-Lecellier, Véronique; Barbier, Michèle; Barker, Katherine; Bertilsson, Stefan; Bicak, Mesude; Bietz, Matthew J; Bobe, Jason; Bodrossy, Levente; Borja, Angel; Coddington, Jonathan; Fuhrman, Jed; Gerdts, Gunnar; Gillespie, Rosemary; Goodwin, Kelly; Hanson, Paul C; Hero, Jean-Marc; Hoekman, David; Jansson, Janet; Jeanthon, Christian; Kao, Rebecca; Klindworth, Anna; Knight, Rob; Kottmann, Renzo; Koo, Michelle S; Kotoulas, Georgios; Lowe, Andrew J; Marteinsson, Viggó Thór; Meyer, Folker; Morrison, Norman; Myrold, David D; Pafilis, Evangelos; Parker, Stephanie; Parnell, John Jacob; Polymenakou, Paraskevi N; Ratnasingham, Sujeevan; Roderick, George K; Rodriguez-Ezpeleta, Naiara; Schonrogge, Karsten; Simon, Nathalie; Valette-Silver, Nathalie J; Springer, Yuri P; Stone, Graham N; Stones-Havas, Steve; Sansone, Susanna-Assunta; Thibault, Kate M; Wecker, Patricia; Wichels, Antje; Wooley, John C; Yahara, Tetsukazu; Zingone, Adriana

    2014-03-07

    The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms.An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated.

  13. The founding charter of the Genomic Observatories Network

    PubMed Central

    2014-01-01

    The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms. An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated. PMID:24606731

  14. Engineering intracellular active transport systems as in vivo biomolecular tools.

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

    Bachand, George David; Carroll-Portillo, Amanda

    2006-11-01

    Active transport systems provide essential functions in terms of cell physiology and metastasis. These systems, however, are also co-opted by invading viruses, enabling directed transport of the virus to and from the cell's nucleus (i.e., the site of virus replication). Based on this concept, fundamentally new approaches for interrogating and manipulating the inner workings of living cells may be achievable by co-opting Nature's active transport systems as an in vivo biomolecular tool. The overall goal of this project was to investigate the ability to engineer kinesin-based transport systems for in vivo applications, specifically the collection of effector proteins (e.g., transcriptionalmore » regulators) within single cells. In the first part of this project, a chimeric fusion protein consisting of kinesin and a single chain variable fragment (scFv) of an antibody was successfully produced through a recombinant expression system. The kinesin-scFv retained both catalytic and antigenic functionality, enabling selective capture and transport of target antigens. The incorporation of a rabbit IgG-specific scFv into the kinesin established a generalized system for functionalizing kinesin with a wide range of target-selective antibodies raised in rabbits. The second objective was to develop methods of isolating the intact microtubule network from live cells as a platform for evaluating kinesin-based transport within the cytoskeletal architecture of a cell. Successful isolation of intact microtubule networks from two distinct cell types was demonstrated using glutaraldehyde and methanol fixation methods. This work provides a platform for inferring the ability of kinesin-scFv to function in vivo, and may also serve as a three-dimensional scaffold for evaluating and exploiting kinesin-based transport for nanotechnological applications. Overall, the technology developed in this project represents a first-step in engineering active transport system for in vivo applications. Further development could potentially enable selective capture of intracellular antigens, targeted delivery of therapeutic agents, or disruption of the transport systems and consequently the infection and pathogenesis cycle of biothreat agents.« less

  15. Synchronization of glycolytic oscillations in a yeast cell population.

    PubMed

    Danø, S; Hynne, F; De Monte, S; d'Ovidio, F; Sørensen, P G; Westerhoff, H

    2001-01-01

    The mechanism of active phase synchronization in a suspension of oscillatory yeast cells has remained a puzzle for almost half a century. The difficulty of the problem stems from the fact that the synchronization phenomenon involves the entire metabolic network of glycolysis and fermentation, and consequently it cannot be addressed at the level of a single enzyme or a single chemical species. In this paper it is shown how this system in a CSTR (continuous flow stirred tank reactor) can be modelled quantitatively as a population of Stuart-Landau oscillators interacting by exchange of metabolites through the extracellular medium, thus reducing the complexity of the problem without sacrificing the biochemical realism. The parameters of the model can be derived by a systematic expansion from any full-scale model of the yeast cell kinetics with a supercritical Hopf bifurcation. Some parameter values can also be obtained directly from analysis of perturbation experiments. In the mean-field limit, equations for the study of populations having a distribution of frequencies are used to simulate the effect of the inherent variations between cells.

  16. The molecular network governing nodule organogenesis and infection in the model legume Lotus japonicus.

    PubMed

    Madsen, Lene H; Tirichine, Leïla; Jurkiewicz, Anna; Sullivan, John T; Heckmann, Anne B; Bek, Anita S; Ronson, Clive W; James, Euan K; Stougaard, Jens

    2010-04-12

    Bacterial infection of interior tissues of legume root nodules is controlled at the epidermal cell layer and is closely coordinated with progressing organ development. Using spontaneous nodulating Lotus japonicus plant mutants to uncouple nodule organogenesis from infection, we have determined the role of 16 genes in these two developmental processes. We show that host-encoded mechanisms control three alternative entry processes operating in the epidermis, the root cortex and at the single cell level. Single cell infection did not involve the formation of trans-cellular infection threads and was independent of host Nod-factor receptors and bacterial Nod-factor signals. In contrast, Nod-factor perception was required for epidermal root hair infection threads, whereas primary signal transduction genes preceding the secondary Ca2+ oscillations have an indirect role. We provide support for the origin of rhizobial infection through direct intercellular epidermal invasion and subsequent evolution of crack entry and root hair invasions observed in most extant legumes.

  17. Effect of Morphologic Features of Neurons on the Extracellular Electric Potential: A Simulation Study Using Cable Theory and Electro-Quasi-Static Equations.

    PubMed

    Bestel, R; Appali, R; van Rienen, U; Thielemann, C

    2017-11-01

    Microelectrode arrays serve as an indispensable tool in electro-physiological research to study the electrical activity of neural cells, enabling measurements of single cell as well as network communication analysis. Recent experimental studies have reported that the neuronal geometry has an influence on electrical signaling and extracellular recordings. However, the corresponding mechanisms are not yet fully understood and require further investigation. Allowing systematic parameter studies, computational modeling provides the opportunity to examine the underlying effects that influence extracellular potentials. In this letter, we present an in silico single cell model to analyze the effect of geometrical variability on the extracellular electric potentials. We describe finite element models of a single neuron with varying geometric complexity in three-dimensional space. The electric potential generation of the neuron is modeled using Hodgkin-Huxley equations. The signal propagation is described with electro-quasi-static equations, and results are compared with corresponding cable equation descriptions. Our results show that both the geometric dimensions and the distribution of ion channels of a neuron are critical factors that significantly influence both the amplitude and shape of extracellular potentials.

  18. Quantitative analysis of circadian single cell oscillations in response to temperature

    PubMed Central

    Kramer, Achim; Herzel, Hanspeter

    2018-01-01

    Body temperature rhythms synchronize circadian oscillations in different tissues, depending on the degree of cellular coupling: the responsiveness to temperature is higher when single circadian oscillators are uncoupled. So far, the role of coupling in temperature responsiveness has only been studied in organotypic tissue slices of the central circadian pacemaker, because it has been assumed that peripheral target organs behave like uncoupled multicellular oscillators. Since recent studies indicate that some peripheral tissues may exhibit cellular coupling as well, we asked whether peripheral network dynamics also influence temperature responsiveness. Using a novel technique for long-term, high-resolution bioluminescence imaging of primary cultured cells, exposed to repeated temperature cycles, we were able to quantitatively measure period, phase, and amplitude of central (suprachiasmatic nuclei neuron dispersals) and peripheral (mouse ear fibroblasts) single cell oscillations in response to temperature. Employing temperature cycles of different lengths, and different cell densities, we found that some circadian characteristics appear cell-autonomous, e.g. period responses, while others seem to depend on the quality/degree of cellular communication, e.g. phase relationships, robustness of the oscillation, and amplitude. Overall, our findings indicate a strong dependence on the cell’s ability for intercellular communication, which is not only true for neuronal pacemakers, but, importantly, also for cells in peripheral tissues. Hence, they stress the importance of comparative studies that evaluate the degree of coupling in a given tissue, before it may be used effectively as a target for meaningful circadian manipulation. PMID:29293562

  19. 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

  20. Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

    PubMed Central

    Huang, Xiwei; Jiang, Yu; Liu, Xu; Xu, Hang; Han, Zhi; Rong, Hailong; Yang, Haiping; Yan, Mei; Yu, Hao

    2016-01-01

    A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT). However, such a system has limited resolution, making it imperative to improve resolution from the system-level using super-resolution (SR) processing. Yet, how to improve resolution towards better cell detection and recognition with low cost of processing resources and without degrading system throughput is still a challenge. In this article, two machine learning based single-frame SR processing types are proposed and compared for lensless blood cell counting, namely the Extreme Learning Machine based SR (ELMSR) and Convolutional Neural Network based SR (CNNSR). Moreover, lensless blood cell counting prototypes using commercial CMOS image sensors and custom designed backside-illuminated CMOS image sensors are demonstrated with ELMSR and CNNSR. When one captured low-resolution lensless cell image is input, an improved high-resolution cell image will be output. The experimental results show that the cell resolution is improved by 4×, and CNNSR has 9.5% improvement over the ELMSR on resolution enhancing performance. The cell counting results also match well with a commercial flow cytometer. Such ELMSR and CNNSR therefore have the potential for efficient resolution improvement in lensless blood cell counting systems towards POCT applications. PMID:27827837

  1. The immunoglobulin-like genetic predetermination of the brain: the protocadherins, blueprint of the neuronal network

    NASA Astrophysics Data System (ADS)

    Hilschmann, N.; Barnikol, H. U.; Barnikol-Watanabe, S.; Götz, H.; Kratzin, H.; Thinnes, F. P.

    2001-01-01

    The morphogenesis of the brain is governed by synaptogenesis. Synaptogenesis in turn is determined by cell adhesion molecules, which bridge the synaptic cleft and, by homophilic contact, decide which neurons are connected and which are not. Because of their enormous diversification in specificities, protocadherins (pcdhα, pcdhβ, pcdhγ), a new class of cadherins, play a decisive role. Surprisingly, the genetic control of the protocadherins is very similar to that of the immunoglobulins. There are three sets of variable (V) genes followed by a corresponding constant (C) gene. Applying the rules of the immunoglobulin genes to the protocadherin genes leads, despite of this similarity, to quite different results in the central nervous system. The lymphocyte expresses one single receptor molecule specifically directed against an outside stimulus. In contrast, there are three specific recognition sites in each neuron, each expressing a different protocadherin. In this way, 4,950 different neurons arising from one stem cell form a neuronal network, in which homophilic contacts can be formed in 52 layers, permitting an enormous number of different connections and restraints between neurons. This network is one module of the central computer of the brain. Since the V-genes are generated during evolution and V-gene translocation during embryogenesis, outside stimuli have no influence on this network. The network is an inborn property of the protocadherin genes. Every circuit produced, as well as learning and memory, has to be based on this genetically predetermined network. This network is so universal that it can cope with everything, even the unexpected. In this respect the neuronal network resembles the recognition sites of the immunoglobulins.

  2. High definition infrared spectroscopic imaging for lymph node histopathology.

    PubMed

    Leslie, L Suzanne; Wrobel, Tomasz P; Mayerich, David; Bindra, Snehal; Emmadi, Rajyasree; Bhargava, Rohit

    2015-01-01

    Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.

  3. The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.

    PubMed

    Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

    2017-01-01

    The recent "deep learning revolution" in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems.

  4. The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding

    PubMed Central

    Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

    2017-01-01

    The recent “deep learning revolution” in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems. PMID:28377709

  5. SCENERY: a web application for (causal) network reconstruction from cytometry data

    PubMed Central

    Papoutsoglou, Georgios; Athineou, Giorgos; Lagani, Vincenzo; Xanthopoulos, Iordanis; Schmidt, Angelika; Éliás, Szabolcs; Tegnér, Jesper

    2017-01-01

    Abstract Flow and mass cytometry technologies can probe proteins as biological markers in thousands of individual cells simultaneously, providing unprecedented opportunities for reconstructing networks of protein interactions through machine learning algorithms. The network reconstruction (NR) problem has been well-studied by the machine learning community. However, the potentials of available methods remain largely unknown to the cytometry community, mainly due to their intrinsic complexity and the lack of comprehensive, powerful and easy-to-use NR software implementations specific for cytometry data. To bridge this gap, we present Single CEll NEtwork Reconstruction sYstem (SCENERY), a web server featuring several standard and advanced cytometry data analysis methods coupled with NR algorithms in a user-friendly, on-line environment. In SCENERY, users may upload their data and set their own study design. The server offers several data analysis options categorized into three classes of methods: data (pre)processing, statistical analysis and NR. The server also provides interactive visualization and download of results as ready-to-publish images or multimedia reports. Its core is modular and based on the widely-used and robust R platform allowing power users to extend its functionalities by submitting their own NR methods. SCENERY is available at scenery.csd.uoc.gr or http://mensxmachina.org/en/software/. PMID:28525568

  6. Fetal brain extracellular matrix boosts neuronal network formation in 3D bioengineered model of cortical brain tissue.

    PubMed

    Sood, Disha; Chwalek, Karolina; Stuntz, Emily; Pouli, Dimitra; Du, Chuang; Tang-Schomer, Min; Georgakoudi, Irene; Black, Lauren D; Kaplan, David L

    2016-01-01

    The extracellular matrix (ECM) constituting up to 20% of the organ volume is a significant component of the brain due to its instructive role in the compartmentalization of functional microdomains in every brain structure. The composition, quantity and structure of ECM changes dramatically during the development of an organism greatly contributing to the remarkably sophisticated architecture and function of the brain. Since fetal brain is highly plastic, we hypothesize that the fetal brain ECM may contain cues promoting neural growth and differentiation, highly desired in regenerative medicine. Thus, we studied the effect of brain-derived fetal and adult ECM complemented with matricellular proteins on cortical neurons using in vitro 3D bioengineered model of cortical brain tissue. The tested parameters included neuronal network density, cell viability, calcium signaling and electrophysiology. Both, adult and fetal brain ECM as well as matricellular proteins significantly improved neural network formation as compared to single component, collagen I matrix. Additionally, the brain ECM improved cell viability and lowered glutamate release. The fetal brain ECM induced superior neural network formation, calcium signaling and spontaneous spiking activity over adult brain ECM. This study highlights the difference in the neuroinductive properties of fetal and adult brain ECM and suggests that delineating the basis for this divergence may have implications for regenerative medicine.

  7. Multi-Parametric Analysis and Modeling of Relationships between Mitochondrial Morphology and Apoptosis

    PubMed Central

    Reis, Yara; Wolf, Thomas; Brors, Benedikt; Hamacher-Brady, Anne; Eils, Roland; Brady, Nathan R.

    2012-01-01

    Mitochondria exist as a network of interconnected organelles undergoing constant fission and fusion. Current approaches to study mitochondrial morphology are limited by low data sampling coupled with manual identification and classification of complex morphological phenotypes. Here we propose an integrated mechanistic and data-driven modeling approach to analyze heterogeneous, quantified datasets and infer relations between mitochondrial morphology and apoptotic events. We initially performed high-content, multi-parametric measurements of mitochondrial morphological, apoptotic, and energetic states by high-resolution imaging of human breast carcinoma MCF-7 cells. Subsequently, decision tree-based analysis was used to automatically classify networked, fragmented, and swollen mitochondrial subpopulations, at the single-cell level and within cell populations. Our results revealed subtle but significant differences in morphology class distributions in response to various apoptotic stimuli. Furthermore, key mitochondrial functional parameters including mitochondrial membrane potential and Bax activation, were measured under matched conditions. Data-driven fuzzy logic modeling was used to explore the non-linear relationships between mitochondrial morphology and apoptotic signaling, combining morphological and functional data as a single model. Modeling results are in accordance with previous studies, where Bax regulates mitochondrial fragmentation, and mitochondrial morphology influences mitochondrial membrane potential. In summary, we established and validated a platform for mitochondrial morphological and functional analysis that can be readily extended with additional datasets. We further discuss the benefits of a flexible systematic approach for elucidating specific and general relationships between mitochondrial morphology and apoptosis. PMID:22272225

  8. The 4D nucleome project.

    PubMed

    Dekker, Job; Belmont, Andrew S; Guttman, Mitchell; Leshyk, Victor O; Lis, John T; Lomvardas, Stavros; Mirny, Leonid A; O'Shea, Clodagh C; Park, Peter J; Ren, Bing; Politz, Joan C Ritland; Shendure, Jay; Zhong, Sheng

    2017-09-13

    The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.

  9. The 4D Nucleome Project

    PubMed Central

    Dekker, Job; Belmont, Andrew S.; Guttman, Mitchell; Leshyk, Victor O.; Lis, John T.; Lomvardas, Stavros; Mirny, Leonid A.; O’Shea, Clodagh C.; Park, Peter J.; Ren, Bing; Ritland Politz, Joan C.; Shendure, Jay; Zhong, Sheng

    2017-01-01

    Preface The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic understanding of how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental approaches will be combined with biophysical modeling to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells. PMID:28905911

  10. Single-Frame Terrain Mapping Software for Robotic Vehicles

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.

    2011-01-01

    This software is a component in an unmanned ground vehicle (UGV) perception system that builds compact, single-frame terrain maps for distribution to other systems, such as a world model or an operator control unit, over a local area network (LAN). Each cell in the map encodes an elevation value, terrain classification, object classification, terrain traversability, terrain roughness, and a confidence value into four bytes of memory. The input to this software component is a range image (from a lidar or stereo vision system), and optionally a terrain classification image and an object classification image, both registered to the range image. The single-frame terrain map generates estimates of the support surface elevation, ground cover elevation, and minimum canopy elevation; generates terrain traversability cost; detects low overhangs and high-density obstacles; and can perform geometry-based terrain classification (ground, ground cover, unknown). A new origin is automatically selected for each single-frame terrain map in global coordinates such that it coincides with the corner of a world map cell. That way, single-frame terrain maps correctly line up with the world map, facilitating the merging of map data into the world map. Instead of using 32 bits to store the floating-point elevation for a map cell, the vehicle elevation is assigned to the map origin elevation and reports the change in elevation (from the origin elevation) in terms of the number of discrete steps. The single-frame terrain map elevation resolution is 2 cm. At that resolution, terrain elevation from 20.5 to 20.5 m (with respect to the vehicle's elevation) is encoded into 11 bits. For each four-byte map cell, bits are assigned to encode elevation, terrain roughness, terrain classification, object classification, terrain traversability cost, and a confidence value. The vehicle s current position and orientation, the map origin, and the map cell resolution are all included in a header for each map. The map is compressed into a vector prior to delivery to another system.

  11. Recent advances in lineage differentiation from stem cells: hurdles and opportunities?

    PubMed Central

    Terryn, Joke; Tricot, Tine; Gajjar, Madhavsai; Verfaillie, Catherine

    2018-01-01

    Pluripotent stem cells have the property of long-term self-renewal and the potential to give rise to descendants of the three germ layers and hence all mature cells in the human body. Therefore, they hold the promise of offering insight not only into human development but also for human disease modeling and regenerative medicine. However, the generation of mature differentiated cells that closely resemble their in vivo counterparts remains challenging. Recent advances in single-cell transcriptomics and computational modeling of gene regulatory networks are revealing a better understanding of lineage commitment and are driving modern genome editing approaches. Additional modification of the chemical microenvironment, as well as the use of bioengineering tools to recreate the cellular, extracellular matrix, and physical characteristics of the niche wherein progenitors and mature cells reside, is now being used to further improve the maturation and functionality of stem cell progeny. PMID:29552337

  12. Programmable single-cell mammalian biocomputers.

    PubMed

    Ausländer, Simon; Ausländer, David; Müller, Marius; Wieland, Markus; Fussenegger, Martin

    2012-07-05

    Synthetic biology has advanced the design of standardized control devices that program cellular functions and metabolic activities in living organisms. Rational interconnection of these synthetic switches resulted in increasingly complex designer networks that execute input-triggered genetic instructions with precision, robustness and computational logic reminiscent of electronic circuits. Using trigger-controlled transcription factors, which independently control gene expression, and RNA-binding proteins that inhibit the translation of transcripts harbouring specific RNA target motifs, we have designed a set of synthetic transcription–translation control devices that could be rewired in a plug-and-play manner. Here we show that these combinatorial circuits integrated a two-molecule input and performed digital computations with NOT, AND, NAND and N-IMPLY expression logic in single mammalian cells. Functional interconnection of two N-IMPLY variants resulted in bitwise intracellular XOR operations, and a combinatorial arrangement of three logic gates enabled independent cells to perform programmable half-subtractor and half-adder calculations. Individual mammalian cells capable of executing basic molecular arithmetic functions isolated or coordinated to metabolic activities in a predictable, precise and robust manner may provide new treatment strategies and bio-electronic interfaces in future gene-based and cell-based therapies.

  13. A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis.

    PubMed

    Weber, Kristoffer; Bartsch, Udo; Stocking, Carol; Fehse, Boris

    2008-04-01

    Functional gene analysis requires the possibility of overexpression, as well as downregulation of one, or ideally several, potentially interacting genes. Lentiviral vectors are well suited for this purpose as they ensure stable expression of complementary DNAs (cDNAs), as well as short-hairpin RNAs (shRNAs), and can efficiently transduce a wide spectrum of cell targets when packaged within the coat proteins of other viruses. Here we introduce a multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors designed according to the "building blocks" principle. Using a wide spectrum of different fluorescent markers, including drug-selectable enhanced green fluorescent protein (eGFP)- and dTomato-blasticidin-S resistance fusion proteins, LeGO vectors allow simultaneous analysis of multiple genes and shRNAs of interest within single, easily identifiable cells. Furthermore, each functional module is flanked by unique cloning sites, ensuring flexibility and individual optimization. The efficacy of these vectors for analyzing multiple genes in a single cell was demonstrated in several different cell types, including hematopoietic, endothelial, and neural stem and progenitor cells, as well as hepatocytes. LeGO vectors thus represent a valuable tool for investigating gene networks using conditional ectopic expression and knock-down approaches simultaneously.

  14. Identification and functional analysis of long non-coding RNAs in human and mouse early embryos based on single-cell transcriptome data

    PubMed Central

    Qiu, Jia-jun; Ren, Zhao-rui; Yan, Jing-bin

    2016-01-01

    Epigenetics regulations have an important role in fertilization and proper embryonic development, and several human diseases are associated with epigenetic modification disorders, such as Rett syndrome, Beckwith-Wiedemann syndrome and Angelman syndrome. However, the dynamics and functions of long non-coding RNAs (lncRNAs), one type of epigenetic regulators, in human pre-implantation development have not yet been demonstrated. In this study, a comprehensive analysis of human and mouse early-stage embryonic lncRNAs was performed based on public single-cell RNA sequencing data. Expression profile analysis revealed that lncRNAs are expressed in a developmental stage–specific manner during human early-stage embryonic development, whereas a more temporal-specific expression pattern was identified in mouse embryos. Weighted gene co-expression network analysis suggested that lncRNAs involved in human early-stage embryonic development are associated with several important functions and processes, such as oocyte maturation, zygotic genome activation and mitochondrial functions. We also found that the network of lncRNAs involved in zygotic genome activation was highly preservative between human and mouse embryos, whereas in other stages no strong correlation between human and mouse embryo was observed. This study provides insight into the molecular mechanism underlying lncRNA involvement in human pre-implantation embryonic development. PMID:27542205

  15. Small-sized PdCu nanocapsules on 3D graphene for high-performance ethanol oxidation

    NASA Astrophysics Data System (ADS)

    HuThese Authors Contributed Equally To This Work., Chuangang; Zhai, Xiangquan; Zhao, Yang; Bian, Ke; Zhang, Jing; Qu, Liangti; Zhang, Huimin; Luo, Hongxia

    2014-02-01

    A one-pot solvothermal process has been developed for direct preparation of PdCu nanocapsules (with a size of ca. 10 nm) on three-dimensional (3D) graphene. Due to the 3D pore-rich network of graphene and the unique hollow structure of PdCu nanocapsules with a wall thickness of ca. 3 nm, the newly-prepared PdCu/3D graphene hybrids activated electrochemically have great electrocatalytic activity towards ethanol oxidation in alkaline media, much better than single-phase Pd and commercial E-TEK 20% Pt/C catalysts promising for application in direct ethanol fuel cells.A one-pot solvothermal process has been developed for direct preparation of PdCu nanocapsules (with a size of ca. 10 nm) on three-dimensional (3D) graphene. Due to the 3D pore-rich network of graphene and the unique hollow structure of PdCu nanocapsules with a wall thickness of ca. 3 nm, the newly-prepared PdCu/3D graphene hybrids activated electrochemically have great electrocatalytic activity towards ethanol oxidation in alkaline media, much better than single-phase Pd and commercial E-TEK 20% Pt/C catalysts promising for application in direct ethanol fuel cells. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05722d

  16. Genes Responsive to Low-Intensity Pulsed Ultrasound in MC3T3-E1 Preosteoblast Cells

    PubMed Central

    Tabuchi, Yoshiaki; Sugahara, Yuuki; Ikegame, Mika; Suzuki, Nobuo; Kitamura, Kei-ichiro; Kondo, Takashi

    2013-01-01

    Although low-intensity pulsed ultrasound (LIPUS) has been shown to enhance bone fracture healing, the underlying mechanism of LIPUS remains to be fully elucidated. Here, to better understand the molecular mechanism underlying cellular responses to LIPUS, we investigated gene expression profiles in mouse MC3T3-E1 preosteoblast cells exposed to LIPUS using high-density oligonucleotide microarrays and computational gene expression analysis tools. Although treatment of the cells with a single 20-min LIPUS (1.5 MHz, 30 mW/cm2) did not affect the cell growth or alkaline phosphatase activity, the treatment significantly increased the mRNA level of Bglap. Microarray analysis demonstrated that 38 genes were upregulated and 37 genes were downregulated by 1.5-fold or more in the cells at 24-h post-treatment. Ingenuity pathway analysis demonstrated that the gene network U (up) contained many upregulated genes that were mainly associated with bone morphology in the category of biological functions of skeletal and muscular system development and function. Moreover, the biological function of the gene network D (down), which contained downregulated genes, was associated with gene expression, the cell cycle and connective tissue development and function. These results should help to further clarify the molecular basis of the mechanisms of the LIPUS response in osteoblast cells. PMID:24252911

  17. 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.

  18. 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

  19. Novel Holistic Approaches for Overcoming Therapy Resistance in Pancreatic and Colon Cancers.

    PubMed

    Sarkar, Fazlul H

    2016-01-01

    Gastrointestinal (GI) cancers, such as of the colon and pancreas, are highly resistant to both standard and targeted therapeutics. Therapy-resistant and heterogeneous GI cancers harbor highly complex signaling networks (the resistome) that resist apoptotic programming. Commonly used gemcitabine or platinum-based regimens fail to induce meaningful (i.e. disease-reversing) perturbations in the resistome, resulting in high rates of treatment failure. The GI cancer resistance networks are, in part, due to interactions between parallel signaling and aberrantly expressed microRNAs (miRNAs) that collectively promote the development and survival of drug-resistant cancer stem cells with epithelial-to-mesenchymal transition (EMT) characteristics. The lack of understanding of the resistance networks associated with this subpopulation of cells as well as reductionist, single protein-/pathway-targeted approaches have made 'effective drug design' a difficult task. We propose that the successful design of novel therapeutic regimens to target drug-resistant GI tumors is only possible if network-based drug avenues and agents, in particular 'natural agents' with no known toxicity, are correctly identified. Natural agents (dietary agents or their synthetic derivatives) can individually alter miRNA profiles, suppress EMT pathways and eliminate cancer stem-like cells that derive from pancreatic cancer and colon cancer, by partially targeting multiple yet meaningful networks within the GI cancer resistome. However, the efficacy of these agents as combinations (e.g. consumed in the diet) against this resistome has never been studied. This short review article provides an overview of the different challenges involved in the understanding of the GI resistome, and how novel computational biology can help in the design of effective therapies to overcome resistance. © 2015 S. Karger AG, Basel.

  20. A bipartite graph of Neuroendocrine System

    NASA Astrophysics Data System (ADS)

    Guo, Zhong-Wei; Zou, Sheng-Rong; Peng, Yu-Jing; Zhou, Ta; Gu, Chang-Gui; He, Da-Ren

    2008-03-01

    We present an empirical investigation on the neuroendocrine system and suggest describe it by a bipartite graph. In the net the cells can be regarded as collaboration acts and the mediators can be regarded as collaboration actors. The act degree stands for the number of the cells that secrete a single mediator. Among them bFGF (the basic fibroblast growth factor) has the largest node act degree. It is the most important mitogenic cytokine, followed by TGF-beta, IL-6, IL1-beta, VEGF, IGF-1and so on. They are critical in neuroendocrine system to maintain bodily healthiness, emotional stabilization and endocrine harmony. The act degree distribution shows a shifted power law (SPL) function forms [1]. The average act degree of neuroendocrine network is h=3.01, It means that each mediator is secreted by three cells on average. The similarity, which stands for the average probability of secreting the same mediators by all neuroendocrine cells, is observed as s=0.14. Our results may be used in the research of the medical treatment of neuroendocrine diseases. [1] Assortativity and act degree distribution of some collaboration networks, Hui Chang, Bei-Bei Su, Yue-Ping Zhou, Daren He, Physica A, 383 (2007) 687-702

  1. Constraint based modeling of metabolism allows finding metabolic cancer hallmarks and identifying personalized therapeutic windows.

    PubMed

    Bordel, Sergio

    2018-04-13

    In order to choose optimal personalized anticancer treatments, transcriptomic data should be analyzed within the frame of biological networks. The best known human biological network (in terms of the interactions between its different components) is metabolism. Cancer cells have been known to have specific metabolic features for a long time and currently there is a growing interest in characterizing new cancer specific metabolic hallmarks. In this article it is presented a method to find personalized therapeutic windows using RNA-seq data and Genome Scale Metabolic Models. This method is implemented in the python library, pyTARG. Our predictions showed that the most anticancer selective (affecting 27 out of 34 considered cancer cell lines and only 1 out of 6 healthy mesenchymal stem cell lines) single metabolic reactions are those involved in cholesterol biosynthesis. Excluding cholesterol biosynthesis, all the considered cell lines can be selectively affected by targeting different combinations (from 1 to 5 reactions) of only 18 metabolic reactions, which suggests that a small subset of drugs or siRNAs combined in patient specific manners could be at the core of metabolism based personalized treatments.

  2. A mathematical model for mesenchymal and chemosensitive cell dynamics.

    PubMed

    Häcker, Anita

    2012-01-01

    The structure of an underlying tissue network has a strong impact on cell dynamics. If, in addition, cells alter the network by mechanical and chemical interactions, their movement is called mesenchymal. Important examples for mesenchymal movement include fibroblasts in wound healing and metastatic tumour cells. This paper is focused on the latter. Based on the anisotropic biphasic theory of Barocas and Tranquillo, which models a fibre network and interstitial solution as two-component fluid, a mathematical model for the interactions of cells with a fibre network is developed. A new description for fibre reorientation is given and orientation-dependent proteolysis is added to the model. With respect to cell dynamics, the equation, based on anisotropic diffusion, is extended by haptotaxis and chemotaxis. The chemoattractants are the solute network fragments, emerging from proteolysis, and the epidermal growth factor which may guide the cells to a blood vessel. Moreover the cell migration is impeded at either high or low network density. This new model enables us to study chemotactic cell migration in a complex fibre network and the consequential network deformation. Numerical simulations for the cell migration and network deformation are carried out in two space dimensions. Simulations of cell migration in underlying tissue networks visualise the impact of the network structure on cell dynamics. In a scenario for fibre reorientation between cell clusters good qualitative agreement with experimental results is achieved. The invasion speeds of cells in an aligned and an isotropic fibre network are compared. © Springer-Verlag 2011

  3. Dynamic changes in neural circuit topology following mild mechanical injury in vitro.

    PubMed

    Patel, Tapan P; Ventre, Scott C; Meaney, David F

    2012-01-01

    Despite its enormous incidence, mild traumatic brain injury is not well understood. One aspect that needs more definition is how the mechanical energy during injury affects neural circuit function. Recent developments in cellular imaging probes provide an opportunity to assess the dynamic state of neural networks with single-cell resolution. In this article, we developed imaging methods to assess the state of dissociated cortical networks exposed to mild injury. We estimated the imaging conditions needed to achieve accurate measures of network properties, and applied these methodologies to evaluate if mild mechanical injury to cortical neurons produces graded changes to either spontaneous network activity or altered network topology. We found that modest injury produced a transient increase in calcium activity that dissipated within 1 h after injury. Alternatively, moderate mechanical injury produced immediate disruption in network synchrony, loss in excitatory tone, and increased modular topology. A calcium-activated neutral protease (calpain) was a key intermediary in these changes; blocking calpain activation restored the network nearly completely to its pre-injury state. Together, these findings show a more complex change in neural circuit behavior than previously reported for mild mechanical injury, and highlight at least one important early mechanism responsible for these changes.

  4. A theory of cerebellar cortex and adaptive motor control based on two types of universal function approximation capability.

    PubMed

    Fujita, Masahiko

    2016-03-01

    Lesions of the cerebellum result in large errors in movements. The cerebellum adaptively controls the strength and timing of motor command signals depending on the internal and external environments of movements. The present theory describes how the cerebellar cortex can control signals for accurate and timed movements. A model network of the cerebellar Golgi and granule cells is shown to be equivalent to a multiple-input (from mossy fibers) hierarchical neural network with a single hidden layer of threshold units (granule cells) that receive a common recurrent inhibition (from a Golgi cell). The weighted sum of the hidden unit signals (Purkinje cell output) is theoretically analyzed regarding the capability of the network to perform two types of universal function approximation. The hidden units begin firing as the excitatory inputs exceed the recurrent inhibition. This simple threshold feature leads to the first approximation theory, and the network final output can be any continuous function of the multiple inputs. When the input is constant, this output becomes stationary. However, when the recurrent unit activity is triggered to decrease or the recurrent inhibition is triggered to increase through a certain mechanism (metabotropic modulation or extrasynaptic spillover), the network can generate any continuous signals for a prolonged period of change in the activity of recurrent signals, as the second approximation theory shows. By incorporating the cerebellar capability of two such types of approximations to a motor system, in which learning proceeds through repeated movement trials with accompanying corrections, accurate and timed responses for reaching the target can be adaptively acquired. Simple models of motor control can solve the motor error vs. sensory error problem, as well as the structural aspects of credit (or error) assignment problem. Two physiological experiments are proposed for examining the delay and trace conditioning of eyelid responses, as well as saccade adaptation, to investigate this novel idea of cerebellar processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Bio-inspired nanocatalysts for the oxygen reduction reaction.

    PubMed

    Grumelli, Doris; Wurster, Benjamin; Stepanow, Sebastian; Kern, Klaus

    2013-01-01

    Electrochemical conversions at fuel cell electrodes are complex processes. In particular, the oxygen reduction reaction has substantial overpotential limiting the electrical power output efficiency. Effective and inexpensive catalytic interfaces are therefore essential for increased performance. Taking inspiration from enzymes, earth-abundant metal centres embedded in organic environments present remarkable catalytic active sites. Here we show that these enzyme-inspired centres can be effectively mimicked in two-dimensional metal-organic coordination networks self-assembled on electrode surfaces. Networks consisting of trimesic acid and bis-pyridyl-bispyrimidine coordinating to single iron and manganese atoms on Au(111) effectively catalyse the oxygen reduction and reveal distinctive catalytic activity in alkaline media. These results demonstrate the potential of surface-engineered metal-organic networks for electrocatalytic conversions. Specifically designed coordination complexes at surfaces inspired by enzyme cofactors represent a new class of nanocatalysts with promising applications in electrocatalysis.

  6. Engineering rules for evaluating the efficiency of multiplexing traffic streams

    NASA Astrophysics Data System (ADS)

    Klincewicz, John G.

    2004-09-01

    It is common, either for a telecommunications service provider or for a corporate enterprise, to have multiple data networks. For example, both an IP network and an ATM or Frame Relay network could be in operation to serve different applications. This can result in parallel transport links between the same two locations, each carrying data traffic under a different protocol. In this paper, we consider some practical engineering rules, for particular situations, to evaluate whether or not it is advantageous to combine these parallel traffic streams onto a single transport link. Combining the streams requires additional overhead (a so-called "cell tax" ) but, in at least some situations, can result in more efficient use of modular transport capacity. Simple graphs can be used to summarize the analysis. Some interesting, and perhaps unexpected, observations can be made.

  7. Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network

    DTIC Science & Technology

    2013-05-26

    public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University

  8. Genetic and Cellular Mechanisms Regulating Anterior Foregut and Esophageal Development

    PubMed Central

    Jacobs, Ian J.; Ku, Wei-Yao; Que, Jianwen

    2012-01-01

    Separation of the single anterior foregut tube into the esophagus and trachea involves cell proliferation and differentiation, as well as dynamic changes in cell-cell adhesion and migration. These biological processes are regulated and coordinated at multiple levels through the interplay of the epithelium and mesenchyme. Genetic studies and in vitro modeling have shed light on relevant regulatory networks that include a number of transcription factors and signaling pathways. These signaling molecules exhibit unique expression patterns and play specific functions in their respective territories before the separation process occurs. Disruption of regulatory networks inevitably leads to defective separation and malformation of the trachea and esophagus and results in the formation of a relatively common birth defect, esophageal atresia with or without tracheoesophageal fistula (EA/TEF). Significantly, some of the signaling pathways and transcription factors involved in anterior foregut separation continue to play important roles in the morphogenesis of the individual organs. In this review, we will focus on new findings related to these different developmental processes and discuss them in the context of developmental disorders (or birth defects) commonly seen in clinics. PMID:22750256

  9. 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

  10. Isolation, Characterization, Cryopreservation of Human Amniotic Stem Cells and Differentiation to Osteogenic and Adipogenic Cells

    PubMed Central

    Gholizadeh-Ghaleh Aziz, Shiva; Pashaei-Asl, Fatima; Fardyazar, Zahra; Pashaiasl, Maryam

    2016-01-01

    Human stem cells and progenitor cells can be used to treat cancer and replace dysfunctional cells within a tissue or organ. The objective of this study was to identify the appropriate cells type in regenerative medicine and targeted therapy. As an alternative to embryonic and bone marrow stem cells, we examined human amniotic fluid stem cells (hAFSCs), one of the potential source of multipotent stem cells isolated from both cell pellet (using single-stage method), and supernatant of human amniotic fluid. Source of isolation and unique property of the cells emphasize that these cells are one of the promising new tools in therapeutic field. Double sources for isolation and availability of the left over samples in diagnostic laboratory at the same time have less legal and ethical concerns compared with embryonic stem cell studies. Cells were isolated, cultured for 18th passage for 6 months and characterized using qPCR and flow cytometry. Cells showed good proliferative ability in culture condition. The cells successfully differentiated into the adipogenic and osteogenic lineages. Based on these findings, amniotic fluid can be considered as an appropriate and convenient source of human amniotic fluid stem cells. These cells provide potential tools for therapeutic applications in the field of regenerative medicine. To get a better understanding of crosstalk between Oct4/NANOG with osteogenesis and adipogenesis, we used network analysis based on Common Targets algorithm and Common Regulators algorithm as well as subnetwork discovery based on gene set enrichment. Network analysis highlighted the possible role of MIR 302A and MIR let-7g. We demonstrated the high expression of MIR 302A and low expression of MIR let7g in hAFSCs by qPCR. PMID:27434028

  11. Polling-Based High-Bit-Rate Packet Transfer in a Microcellular Network to Allow Fast Terminals

    NASA Astrophysics Data System (ADS)

    Hoa, Phan Thanh; Lambertsen, Gaute; Yamada, Takahiko

    A microcellular network will be a good candidate for the future broadband mobile network. It is expected to support high-bit-rate connection for many fast mobile users if the handover is processed fast enough to lessen its impact on QoS requirements. One of the promising techniques is believed to use for the wireless interface in such a microcellular network is the WLAN (Wireless LAN) technique due to its very high wireless channel rate. However, the less capability of mobility support of this technique must be improved to be able to expand its utilization for the microcellular environment. The reason of its less support mobility is large handover latency delay caused by contention-based handover to the new BS (base station) and delay of re-forwarding data from the old to new BS. This paper presents a proposal of multi-polling and dynamic LMC (Logical Macro Cell) to reduce mentioned above delays. Polling frame for an MT (Mobile Terminal) is sent from every BS belonging to the same LMC — a virtual single macro cell that is a multicast group of several adjacent micro-cells in which an MT is communicating. Instead of contending for the medium of a new BS during handover, the MT responds to the polling sent from that new BS to enable the transition. Because only one BS of the LMC receives the polling ACK (acknowledgement) directly from the MT, this ACK frame has to be multicast to all BSs of the same LMC through the terrestrial network to continue sending the next polling cycle at each BS. Moreover, when an MT hands over to a new cell, its current LMC is switched over to a newly corresponding LMC to prevent the future contending for a new LMC. By this way, an MT can do handover between micro-cells of an LMC smoothly because the redundant resource is reserved for it at neighboring cells, no need to contend with others. Our simulation results using the OMNeT++ simulator illustrate the performance achievements of the multi-polling and dynamic LMC scheme in eliminating handover latency, packet loss and keeping mobile users' throughput stable in the high traffic load condition though it causes somewhat overhead on the neighboring cells.

  12. Recapitulating in vivo-like plasticity of glioma cell invasion along blood vessels and in astrocyte-rich stroma.

    PubMed

    Gritsenko, Pavlo; Leenders, William; Friedl, Peter

    2017-10-01

    Diffuse invasion of glioma cells into the brain parenchyma leads to nonresectable brain tumors and poor prognosis of glioma disease. In vivo, glioma cells can adopt a range of invasion strategies and routes, by moving as single cells, collective strands and multicellular networks along perivascular, perineuronal and interstitial guidance cues. Current in vitro assays to probe glioma cell invasion, however, are limited in recapitulating the modes and adaptability of glioma invasion observed in brain parenchyma, including collective behaviours. To mimic in vivo-like glioma cell invasion in vitro, we here applied three tissue-inspired 3D environments combining multicellular glioma spheroids and reconstituted microanatomic features of vascular and interstitial brain structures. Radial migration from multicellular glioma spheroids of human cell lines and patient-derived xenograft cells was monitored using (1) reconstituted basement membrane/hyaluronan interfaces representing the space along brain vessels; (2) 3D scaffolds generated by multi-layered mouse astrocytes to reflect brain interstitium; and (3) freshly isolated mouse brain slice culture ex vivo. The invasion patterns in vitro were validated using histological analysis of brain sections from glioblastoma patients and glioma xenografts infiltrating the mouse brain. Each 3D assay recapitulated distinct aspects of major glioma invasion patterns identified in mouse xenografts and patient brain samples, including individually migrating cells, collective strands extending along blood vessels, and multicellular networks of interconnected glioma cells infiltrating the neuropil. In conjunction, these organotypic assays enable a range of invasion modes used by glioma cells and will be applicable for mechanistic analysis and targeting of glioma cell dissemination.

  13. Bistability: Requirements on Cell-Volume, Protein Diffusion, and Thermodynamics

    PubMed Central

    Endres, Robert G.

    2015-01-01

    Bistability is considered wide-spread among bacteria and eukaryotic cells, useful e.g. for enzyme induction, bet hedging, and epigenetic switching. However, this phenomenon has mostly been described with deterministic dynamic or well-mixed stochastic models. Here, we map known biological bistable systems onto the well-characterized biochemical Schlögl model, using analytical calculations and stochastic spatiotemporal simulations. In addition to network architecture and strong thermodynamic driving away from equilibrium, we show that bistability requires fine-tuning towards small cell volumes (or compartments) and fast protein diffusion (well mixing). Bistability is thus fragile and hence may be restricted to small bacteria and eukaryotic nuclei, with switching triggered by volume changes during the cell cycle. For large volumes, single cells generally loose their ability for bistable switching and instead undergo a first-order phase transition. PMID:25874711

  14. Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

    PubMed

    Aguiar, Manuela A D; Dias, Ana Paula S; Ferreira, Flora

    2017-01-01

    We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

  15. Doppler Radar and Lightning Network Observations of a Severe Outbreak of Tropical Cyclone Tornadoes

    NASA Technical Reports Server (NTRS)

    Mccaul, Eugene W., Jr.; Buechler, Dennis E.; Goodman, Steven J.; Cammarata, Michael

    2004-01-01

    Data from a single Weather Surveillance Radar-1988 Doppler (WSR-88D) and the National Lightning Detection Network are used to examine the characteristics of the convective storms that produced a severe tornado outbreak, including three tornadoes that reached F3 intensity, within Tropical Storm Beryl s remnants on 16 August 1994. Comparison of the radar data with reports of tornadoes suggests that only 13 cells produced the 29 tornadoes that were documented in Georgia and the Carolinas on that date. Six of these cells spawned multiple tornadoes, and the radar data confirm the presence of miniature supercells. One of the cells was identifiable on radar for 11 h. spawning tornadoes over a time period spanning approximately 6.5 h. Several other tornadic cells also exhibited great longevity, with cell lifetimes longer than ever previously documented in a landfalling tropical cyclone (TC) tornado event. This event is easily the most intense TC tornado outbreak yet documented with WSR-88Ds. Time-height analyses of the three strongest tornadic supercells are presented in order to document storm kinematic structure and to show how these storms appear at different ranges from a WSR-88D. In addition, cloud-to-ground (CG) lightning data are examined in Beryl s remnants. Although the tornadic cells were responsible for most of Beryl's CG lightning, their flash rates were only weak to moderate, and in all the tornadic storms the lightning flashes were almost entirely negative in polarity. A few of the single-tornado storms produced no detectable CG lightning at all. There is evidence that CG lightning rates decreased during the tornadoes, compared to 30-min periods before the tornadoes. A number of the storms spawned tornadoes just after producing their final CG lightning flashes. Contrary to the findings for flash rates, both peak currents and positive flash percentages were larger in Beryl's nontornadic storms than in the tornadic ones.

  16. Tropomodulin 1 Regulation of Actin Is Required for the Formation of Large Paddle Protrusions Between Mature Lens Fiber Cells

    PubMed Central

    Cheng, Catherine; Nowak, Roberta B.; Biswas, Sondip K.; Lo, Woo-Kuen; FitzGerald, Paul G.; Fowler, Velia M.

    2016-01-01

    Purpose To elucidate the proteins required for specialized small interlocking protrusions and large paddle domains at lens fiber cell tricellular junctions (vertices), we developed a novel method to immunostain single lens fibers and studied changes in cell morphology due to loss of tropomodulin 1 (Tmod1), an F-actin pointed end–capping protein. Methods We investigated F-actin and F-actin–binding protein localization in interdigitations of Tmod1+/+ and Tmod1−/− single mature lens fibers. Results F-actin–rich small protrusions and large paddles were present along cell vertices of Tmod1+/+ mature fibers. In contrast, Tmod1−/− mature fiber cells lack normal paddle domains, while small protrusions were unaffected. In Tmod1+/+ mature fibers, Tmod1, β2-spectrin, and α-actinin are localized in large puncta in valleys between paddles; but in Tmod1−/− mature fibers, β2-spectrin was dispersed while α-actinin was redistributed at the base of small protrusions and rudimentary paddles. Fimbrin and Arp3 (actin-related protein 3) were located in puncta at the base of small protrusions, while N-cadherin and ezrin outlined the cell membrane in both Tmod1+/+ and Tmod1−/− mature fibers. Conclusions These results suggest that distinct F-actin organizations are present in small protrusions versus large paddles. Formation and/or maintenance of large paddle domains depends on a β2-spectrin–actin network stabilized by Tmod1. α-Actinin–crosslinked F-actin bundles are enhanced in absence of Tmod1, indicating altered cytoskeleton organization. Formation of small protrusions is likely facilitated by Arp3-branched and fimbrin-bundled F-actin networks, which do not depend on Tmod1. This is the first work to reveal the F-actin–associated proteins required for the formation of paddles between lens fibers. PMID:27537257

  17. Micromechanics of human mitotic chromosomes

    NASA Astrophysics Data System (ADS)

    Sun, Mingxuan; Kawamura, Ryo; Marko, John F.

    2011-02-01

    Eukaryote cells dramatically reorganize their long chromosomal DNAs to facilitate their physical segregation during mitosis. The internal organization of folded mitotic chromosomes remains a basic mystery of cell biology; its understanding would likely shed light on how chromosomes are separated from one another as well as into chromosome structure between cell divisions. We report biophysical experiments on single mitotic chromosomes from human cells, where we combine micromanipulation, nano-Newton-scale force measurement and biochemical treatments to study chromosome connectivity and topology. Results are in accord with previous experiments on amphibian chromosomes and support the 'chromatin network' model of mitotic chromosome structure. Prospects for studies of chromosome-organizing proteins using siRNA expression knockdowns, as well as for differential studies of chromosomes with and without mutations associated with genetic diseases, are also discussed.

  18. A Single Multiplex crRNA Array for FnCpf1-Mediated Human Genome Editing.

    PubMed

    Sun, Huihui; Li, Fanfan; Liu, Jie; Yang, Fayu; Zeng, Zhenhai; Lv, Xiujuan; Tu, Mengjun; Liu, Yeqing; Ge, Xianglian; Liu, Changbao; Zhao, Junzhao; Zhang, Zongduan; Qu, Jia; Song, Zongming; Gu, Feng

    2018-06-15

    Cpf1 has been harnessed as a tool for genome manipulation in various species because of its simplicity and high efficiency. Our recent study demonstrated that FnCpf1 could be utilized for human genome editing with notable advantages for target sequence selection due to the flexibility of the protospacer adjacent motif (PAM) sequence. Multiplex genome editing provides a powerful tool for targeting members of multigene families, dissecting gene networks, modeling multigenic disorders in vivo, and applying gene therapy. However, there are no reports at present that show FnCpf1-mediated multiplex genome editing via a single customized CRISPR RNA (crRNA) array. In the present study, we utilize a single customized crRNA array to simultaneously target multiple genes in human cells. In addition, we also demonstrate that a single customized crRNA array to target multiple sites in one gene could be achieved. Collectively, FnCpf1, a powerful genome-editing tool for multiple genomic targets, can be harnessed for effective manipulation of the human genome. Copyright © 2018 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

  19. Convergence of Cortical and Sensory Driver Inputs on Single Thalamocortical Cells

    PubMed Central

    Groh, Alexander; Bokor, Hajnalka; Mease, Rebecca A.; Plattner, Viktor M.; Hangya, Balázs; Stroh, Albrecht; Deschenes, Martin; Acsády, László

    2014-01-01

    Ascending and descending information is relayed through the thalamus via strong, “driver” pathways. According to our current knowledge, different driver pathways are organized in parallel streams and do not interact at the thalamic level. Using an electron microscopic approach combined with optogenetics and in vivo physiology, we examined whether driver inputs arising from different sources can interact at single thalamocortical cells in the rodent somatosensory thalamus (nucleus posterior, POm). Both the anatomical and the physiological data demonstrated that ascending driver inputs from the brainstem and descending driver inputs from cortical layer 5 pyramidal neurons converge and interact on single thalamocortical neurons in POm. Both individual pathways displayed driver properties, but they interacted synergistically in a time-dependent manner and when co-activated, supralinearly increased the output of thalamus. As a consequence, thalamocortical neurons reported the relative timing between sensory events and ongoing cortical activity. We conclude that thalamocortical neurons can receive 2 powerful inputs of different origin, rather than only a single one as previously suggested. This allows thalamocortical neurons to integrate raw sensory information with powerful cortical signals and transfer the integrated activity back to cortical networks. PMID:23825316

  20. Magnetic nanoparticles-loaded Physarum polycephalum: Directed growth and particles distribution.

    PubMed

    Dimonte, Alice; Cifarelli, Angelica; Berzina, Tatiana; Chiesi, Valentina; Ferro, Patrizia; Besagni, Tullo; Albertini, Franca; Adamatzky, Andrew; Erokhin, Victor

    2014-11-06

    Slime mold Physarum polycephalum is a single cell visible by an unaided eye. The slime mold optimizes its network of protoplasmic tubes to minimize expose to repellents and maximize expose to attractants and to make efficient transportation of nutrients. These properties of P. polycephalum, together with simplicity of its handling and culturing, make it a priceless substrate for designing novel sensing, computing and actuating architectures in living amorphous biological substrate. We demonstrate that, by loading Physarum with magnetic particles and positioning it in a magnetic field, we can, in principle, impose analog control procedures to precisely route active growing zones of slime mold and shape topology of its protoplasmic networks.

  1. Magnetic Nanoparticles-Loaded Physarum polycephalum: Directed Growth and Particles Distribution.

    PubMed

    Dimonte, Alice; Cifarelli, Angelica; Berzina, Tatiana; Chiesi, Valentina; Ferro, Patrizia; Besagni, Tullo; Albertini, Franca; Adamatzky, Andrew; Erokhin, Victor

    2015-12-01

    Slime mold Physarum polycephalum is a single cell visible by an unaided eye. The slime mold optimizes its network of protoplasmic tubes to minimize expose to repellents and maximize expose to attractants and to make efficient transportation of nutrients. These properties of P. polycephalum, together with simplicity of its handling and culturing, make it a priceless substrate for designing novel sensing, computing and actuating architectures in living amorphous biological substrate. We demonstrate that, by loading Physarum with magnetic particles and positioning it in a magnetic field, we can, in principle, impose analog control procedures to precisely route active growing zones of slime mold and shape topology of its protoplasmic networks.

  2. Genome-wide bisulfite sensitivity profiling of yeast suggests bisulfite inhibits transcription.

    PubMed

    Segovia, Romulo; Mathew, Veena; Tam, Annie S; Stirling, Peter C

    2017-09-01

    Bisulfite, in the form of sodium bisulfite or metabisulfite, is used commercially as a food preservative. Bisulfite is used in the laboratory as a single-stranded DNA mutagen in epigenomic analyses of DNA methylation. Recently it has also been used on whole yeast cells to induce mutations in exposed single-stranded regions in vivo. To understand the effects of bisulfite on live cells we conducted a genome-wide screen for bisulfite sensitive mutants in yeast. Screening the deletion mutant array, and collections of essential gene mutants we define a genetic network of bisulfite sensitive mutants. Validation of screen hits revealed hyper-sensitivity of transcription and RNA processing mutants, rather than DNA repair pathways and follow-up analyses support a role in perturbation of RNA transactions. We propose a model in which bisulfite-modified nucleotides may interfere with transcription or RNA metabolism when used in vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Rapid learning in visual cortical networks.

    PubMed

    Wang, Ye; Dragoi, Valentin

    2015-08-26

    Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

  4. Immunodetection and intracellular localization of caldesmon-like proteins in Amoeba proteus.

    PubMed

    Gagola, M; Kłopocka, W; Greebecki, A; Makuch, R

    2003-09-01

    Caldesmon immunoanalogues were detected in Amoeba proteus cell homogenates by the Western blot technique. Three immunoreactive bands were recognized by polyclonal antibodies against the whole molecule of chicken gizzard caldesmon as well as by a monoclonal antibody against its C-terminal domain: one major and two minor bands corresponding to proteins with apparent molecular masses of 150, 69, and 60 kDa. The presence of caldesmon-like protein(s) in amoebae was revealed as well in single cells after their fixation, staining with the same antibodies, and recording their total fluorescence in a confocal laser scanning microscope. Proteins recognized by the antibodies bind to filamentous actin. This was established by a cosedimentation assay in cell homogenates and by colocalization of the caldesmon-related immunofluorescence with the fluorescence of filamentous actin stained with rhodamine-labelled phalloidin, demonstrated in optical sections of single cells in a confocal microscope. Caldesmon is colocalized with filamentous actin in the withdrawn cell regions where the cortical actomyosin network contracts and actin is depolymerized, in the frontal zone where actin is polymerized again and the cortical cytoskeleton is reconstructed, inside the nucleus and in the perinuclear cytoskeleton, and probably at the cell-to-substratum adhesion sites. The regulatory role of caldesmon in these functionally different regions of locomoting amoebae is discussed.

  5. Stabilization of perturbed Boolean network attractors through compensatory interactions

    PubMed Central

    2014-01-01

    Background Understanding and ameliorating the effects of network damage are of significant interest, due in part to the variety of applications in which network damage is relevant. For example, the effects of genetic mutations can cascade through within-cell signaling and regulatory networks and alter the behavior of cells, possibly leading to a wide variety of diseases. The typical approach to mitigating network perturbations is to consider the compensatory activation or deactivation of system components. Here, we propose a complementary approach wherein interactions are instead modified to alter key regulatory functions and prevent the network damage from triggering a deregulatory cascade. Results We implement this approach in a Boolean dynamic framework, which has been shown to effectively model the behavior of biological regulatory and signaling networks. We show that the method can stabilize any single state (e.g., fixed point attractors or time-averaged representations of multi-state attractors) to be an attractor of the repaired network. We show that the approach is minimalistic in that few modifications are required to provide stability to a chosen attractor and specific in that interventions do not have undesired effects on the attractor. We apply the approach to random Boolean networks, and further show that the method can in some cases successfully repair synchronous limit cycles. We also apply the methodology to case studies from drought-induced signaling in plants and T-LGL leukemia and find that it is successful in both stabilizing desired behavior and in eliminating undesired outcomes. Code is made freely available through the software package BooleanNet. Conclusions The methodology introduced in this report offers a complementary way to manipulating node expression levels. A comprehensive approach to evaluating network manipulation should take an "all of the above" perspective; we anticipate that theoretical studies of interaction modification, coupled with empirical advances, will ultimately provide researchers with greater flexibility in influencing system behavior. PMID:24885780

  6. Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

    PubMed

    Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

    2017-10-03

    In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  7. Optimal actuator location within a morphing wing scissor mechanism configuration

    NASA Astrophysics Data System (ADS)

    Joo, James J.; Sanders, Brian; Johnson, Terrence; Frecker, Mary I.

    2006-03-01

    In this paper, the optimal location of a distributed network of actuators within a scissor wing mechanism is investigated. The analysis begins by developing a mechanical understanding of a single cell representation of the mechanism. This cell contains four linkages connected by pin joints, a single actuator, two springs to represent the bidirectional behavior of a flexible skin, and an external load. Equilibrium equations are developed using static analysis and the principle of virtual work equations. An objective function is developed to maximize the efficiency of the unit cell model. It is defined as useful work over input work. There are two constraints imposed on this problem. The first is placed on force transferred from the external source to the actuator. It should be less than the blocked actuator force. The other is to require the ratio of output displacement over input displacement, i.e., geometrical advantage (GA), of the cell to be larger than a prescribed value. Sequential quadratic programming is used to solve the optimization problem. This process suggests a systematic approach to identify an optimum location of an actuator and to avoid the selection of location by trial and error. Preliminary results show that optimum locations of an actuator can be selected out of feasible regions according to the requirements of the problem such as a higher GA, a higher efficiency, or a smaller transferred force from external force. Results include analysis of single and multiple cell wing structures and some experimental comparisons.

  8. A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons.

    PubMed

    Beim Graben, Peter; Rodrigues, Serafim

    2012-01-01

    We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement.

  9. Clique of Functional Hubs Orchestrates Population Bursts in Developmentally Regulated Neural Networks

    PubMed Central

    Luccioli, Stefano; Ben-Jacob, Eshel; Barzilai, Ari; Bonifazi, Paolo; Torcini, Alessandro

    2014-01-01

    It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrate population activity. PMID:25255443

  10. Neurons with hysteresis form a network that can learn without any changes in synaptic connection strengths

    NASA Astrophysics Data System (ADS)

    Hoffmann, Geoffrey W.; Benson, Maurice W.

    1986-08-01

    A neural network concept derived from an analogy between the immune system and the central nerous system is outlined. The theory is based on a nervous that is slightly more complicated than the conventional McCullogh-Pitts type of neuron, in that it exhibits hysteresis at the single cell level. This added complication is compensated by the fact that a network of such neurons is able to learn without the necessity for any changes in synaptic connection strengths. The learning occurs as a natural consequence of interactions between the network and its enviornment, with environmental stimuli moving the system around in an N-dimensional phase space, until a point in phase space is reached such that the system's responses are appropriate for dealing with the stimuli. Due to the hysteresis associated with each neuron, the system tends to stay in the region of phase space where it is located. The theory includes a role for sleep in learning.

  11. A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons

    PubMed Central

    beim Graben, Peter; Rodrigues, Serafim

    2013-01-01

    We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the “open-field” configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement. PMID:23316157

  12. Human astrocytic grid networks patterned in parylene-C inlayed SiO2 trenches.

    PubMed

    Jordan, M D; Raos, B J; Bunting, A S; Murray, A F; Graham, E S; Unsworth, C P

    2016-10-01

    Recent literature suggests that glia, and in particular astrocytes, should be studied as organised networks which communicate through gap junctions. Astrocytes, however, adhere to most surfaces and are highly mobile cells. In order to study, such organised networks effectively in vitro it is necessary to influence them to pattern to certain substrates whilst being repelled from others and to immobilise the astrocytes sufficiently such that they do not continue to migrate further whilst under study. In this article, we demonstrate for the first time how it is possible to facilitate the study of organised patterned human astrocytic networks using hNT astrocytes in a SiO2 trench grid network that is inlayed with the biocompatible material, parylene-C. We demonstrate how the immobilisation of astrocytes lies in the depth of the SiO2 trench, determining an optimum trench depth and that the optimum patterning of astrocytes is a consequence of the parylene-C inlay and the grid node spacing. We demonstrate high fidelity of the astrocytic networks and demonstrate that functionality of the hNT astrocytes through ATP evoked calcium signalling is also dependent on the grid node spacing. Finally, we demonstrate that the location of the nuclei on the grid nodes is also a function of the grid node spacing. The significance of this work, is to describe a suitable platform to facilitate the study of hNT astrocytes from the single cell level to the network level to improve knowledge and understanding of how communication links to spatial organisation at these higher order scales and trigger in vitro research further in this area with clinical applications in the area of epilepsy, stroke and focal cerebral ischemia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Linear time-varying models can reveal non-linear interactions of biomolecular regulatory networks using multiple time-series data.

    PubMed

    Kim, Jongrae; Bates, Declan G; Postlethwaite, Ian; Heslop-Harrison, Pat; Cho, Kwang-Hyun

    2008-05-15

    Inherent non-linearities in biomolecular interactions make the identification of network interactions difficult. One of the principal problems is that all methods based on the use of linear time-invariant models will have fundamental limitations in their capability to infer certain non-linear network interactions. Another difficulty is the multiplicity of possible solutions, since, for a given dataset, there may be many different possible networks which generate the same time-series expression profiles. A novel algorithm for the inference of biomolecular interaction networks from temporal expression data is presented. Linear time-varying models, which can represent a much wider class of time-series data than linear time-invariant models, are employed in the algorithm. From time-series expression profiles, the model parameters are identified by solving a non-linear optimization problem. In order to systematically reduce the set of possible solutions for the optimization problem, a filtering process is performed using a phase-portrait analysis with random numerical perturbations. The proposed approach has the advantages of not requiring the system to be in a stable steady state, of using time-series profiles which have been generated by a single experiment, and of allowing non-linear network interactions to be identified. The ability of the proposed algorithm to correctly infer network interactions is illustrated by its application to three examples: a non-linear model for cAMP oscillations in Dictyostelium discoideum, the cell-cycle data for Saccharomyces cerevisiae and a large-scale non-linear model of a group of synchronized Dictyostelium cells. The software used in this article is available from http://sbie.kaist.ac.kr/software

  14. Cross-species transcriptional network analysis reveals conservation and variation in response to metal stress in cyanobacteria

    PubMed Central

    2013-01-01

    Background As one of the most dominant bacterial groups on Earth, cyanobacteria play a pivotal role in the global carbon cycling and the Earth atmosphere composition. Understanding their molecular responses to environmental perturbations has important scientific and environmental values. Since important biological processes or networks are often evolutionarily conserved, the cross-species transcriptional network analysis offers a useful strategy to decipher conserved and species-specific transcriptional mechanisms that cells utilize to deal with various biotic and abiotic disturbances, and it will eventually lead to a better understanding of associated adaptation and regulatory networks. Results In this study, the Weighted Gene Co-expression Network Analysis (WGCNA) approach was used to establish transcriptional networks for four important cyanobacteria species under metal stress, including iron depletion and high copper conditions. Cross-species network comparison led to discovery of several core response modules and genes possibly essential to metal stress, as well as species-specific hub genes for metal stresses in different cyanobacteria species, shedding light on survival strategies of cyanobacteria responding to different environmental perturbations. Conclusions The WGCNA analysis demonstrated that the application of cross-species transcriptional network analysis will lead to novel insights to molecular response to environmental changes which will otherwise not be achieved by analyzing data from a single species. PMID:23421563

  15. Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation

    PubMed Central

    Planas, Delphine; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R. M.

    2017-01-01

    HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation. PMID:28727807

  16. Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

    PubMed

    Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

    2014-01-01

    Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

  17. Spatio-temporal specialization of GABAergic septo-hippocampal neurons for rhythmic network activity.

    PubMed

    Unal, Gunes; Crump, Michael G; Viney, Tim J; Éltes, Tímea; Katona, Linda; Klausberger, Thomas; Somogyi, Peter

    2018-03-03

    Medial septal GABAergic neurons of the basal forebrain innervate the hippocampus and related cortical areas, contributing to the coordination of network activity, such as theta oscillations and sharp wave-ripple events, via a preferential innervation of GABAergic interneurons. Individual medial septal neurons display diverse activity patterns, which may be related to their termination in different cortical areas and/or to the different types of innervated interneurons. To test these hypotheses, we extracellularly recorded and juxtacellularly labeled single medial septal neurons in anesthetized rats in vivo during hippocampal theta and ripple oscillations, traced their axons to distant cortical target areas, and analyzed their postsynaptic interneurons. Medial septal GABAergic neurons exhibiting different hippocampal theta phase preferences and/or sharp wave-ripple related activity terminated in restricted hippocampal regions, and selectively targeted a limited number of interneuron types, as established on the basis of molecular markers. We demonstrate the preferential innervation of bistratified cells in CA1 and of basket cells in CA3 by individual axons. One group of septal neurons was suppressed during sharp wave-ripples, maintained their firing rate across theta and non-theta network states and mainly fired along the descending phase of CA1 theta oscillations. In contrast, neurons that were active during sharp wave-ripples increased their firing significantly during "theta" compared to "non-theta" states, with most firing during the ascending phase of theta oscillations. These results demonstrate that specialized septal GABAergic neurons contribute to the coordination of network activity through parallel, target area- and cell type-selective projections to the hippocampus.

  18. Metro-access integrated network based on optical OFDMA with dynamic sub-carrier allocation and power distribution.

    PubMed

    Zhang, Chongfu; Zhang, Qiongli; Chen, Chen; Jiang, Ning; Liu, Deming; Qiu, Kun; Liu, Shuang; Wu, Baojian

    2013-01-28

    We propose and demonstrate a novel optical orthogonal frequency-division multiple access (OFDMA)-based metro-access integrated network with dynamic resource allocation. It consists of a single fiber OFDMA ring and many single fiber OFDMA trees, which transparently integrates metropolitan area networks with optical access networks. The single fiber OFDMA ring connects the core network and the central nodes (CNs), the CNs are on demand reconfigurable and use multiple orthogonal sub-carriers to realize parallel data transmission and dynamic resource allocation, meanwhile, they can also implement flexible power distribution. The remote nodes (RNs) distributed in the user side are connected by the single fiber OFDMA trees with the corresponding CN. The obtained results indicate that our proposed metro-access integrated network is feasible and the power distribution is agile.

  19. On creativity of slime mould

    NASA Astrophysics Data System (ADS)

    Adamatzky, Andrew; Armstrong, Rachel; Jones, Jeff; Gunji, Yukio-Pegio

    2013-07-01

    Slime mould Physarum polycephalum is large single cell with intriguingly smart behaviour. The slime mould shows outstanding abilities to adapt its protoplasmic network to varying environmental conditions. The slime mould can solve tasks of computational geometry, image processing, logics and arithmetics when data are represented by configurations of attractants and repellents. We attempt to map behavioural patterns of slime onto the cognitive control vs. schizotypy spectrum phase space and thus interpret slime mould's activity in terms of creativity.

  20. In-situ immobilization of quantum dots in polysaccharide-based nanogels for integration of optical pH-sensing, tumor cell imaging, and drug delivery.

    PubMed

    Wu, Weitai; Aiello, Michael; Zhou, Ting; Berliner, Alexandra; Banerjee, Probal; Zhou, Shuiqin

    2010-04-01

    We report a class of polysaccharide-based hybrid nanogels that can integrate the functional building blocks for optical pH-sensing, cancer cell imaging, and controlled drug release into a single nanoparticle system, which can offer broad opportunities for combined diagnosis and therapy. The hybrid nanogels were prepared by in-situ immobilization of CdSe quantum dots (QDs) in the interior of the pH and temperature dual responsive hydroxypropylcellulose-poly(acrylic acid) (HPC-PAA) semi-interpenetrating polymer networks. The-OH groups of the HPC chains are designed to sequester the precursor Cd(2+) ions into the nanogels as well as stabilize the in-situ formed CdSe QDs. The pH-sensitive PAA network chains are designed to induce a pH-responsive volume phase transition of the hybrid nanogels. The developed HPC-PAA-CdSe hybrid nanogels combine a strong trap emission at 741nm for sensing physicochemical environment in a pH dependent manner and a visible excitonic emission at 592nm for mouse melanoma B16F10 cell imaging. The hybrid nanogels also provide excellent stability as a drug carrier, which cannot only provide a high drug loading capacity for a model anticancer drug temozolomide, but also offer a pH-triggered sustained-release of the drug molecules in the gel network. Copyright 2010 Elsevier Ltd. All rights reserved.

  1. In vivo genome-wide analysis of multiple tissues identifies gene regulatory networks, novel functions and downstream regulatory genes for Bapx1 and its co-regulation with Sox9 in the mammalian vertebral column.

    PubMed

    Chatterjee, Sumantra; Sivakamasundari, V; Yap, Sook Peng; Kraus, Petra; Kumar, Vibhor; Xing, Xing; Lim, Siew Lan; Sng, Joel; Prabhakar, Shyam; Lufkin, Thomas

    2014-12-05

    Vertebrate organogenesis is a highly complex process involving sequential cascades of transcription factor activation or repression. Interestingly a single developmental control gene can occasionally be essential for the morphogenesis and differentiation of tissues and organs arising from vastly disparate embryological lineages. Here we elucidated the role of the mammalian homeobox gene Bapx1 during the embryogenesis of five distinct organs at E12.5 - vertebral column, spleen, gut, forelimb and hindlimb - using expression profiling of sorted wildtype and mutant cells combined with genome wide binding site analysis. Furthermore we analyzed the development of the vertebral column at the molecular level by combining transcriptional profiling and genome wide binding data for Bapx1 with similarly generated data sets for Sox9 to assemble a detailed gene regulatory network revealing genes previously not reported to be controlled by either of these two transcription factors. The gene regulatory network appears to control cell fate decisions and morphogenesis in the vertebral column along with the prevention of premature chondrocyte differentiation thus providing a detailed molecular view of vertebral column development.

  2. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

    PubMed Central

    Gerstner, Wulfram

    2017-01-01

    Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

  3. Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

    PubMed

    Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

    2016-04-01

    River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

  4. Diagnosing phenotypes of single-sample individuals by edge biomarkers.

    PubMed

    Zhang, Wanwei; Zeng, Tao; Liu, Xiaoping; Chen, Luonan

    2015-06-01

    Network or edge biomarkers are a reliable form to characterize phenotypes or diseases. However, obtaining edges or correlations between molecules for an individual requires measurement of multiple samples of that individual, which are generally unavailable in clinical practice. Thus, it is strongly demanded to diagnose a disease by edge or network biomarkers in one-sample-for-one-individual context. Here, we developed a new computational framework, EdgeBiomarker, to integrate edge and node biomarkers to diagnose phenotype of each single test sample. By applying the method to datasets of lung and breast cancer, it reveals new marker genes/gene-pairs and related sub-networks for distinguishing earlier and advanced cancer stages. Our method shows advantages over traditional methods: (i) edge biomarkers extracted from non-differentially expressed genes achieve better cross-validation accuracy of diagnosis than molecule or node biomarkers from differentially expressed genes, suggesting that certain pathogenic information is only present at the level of network and under-estimated by traditional methods; (ii) edge biomarkers categorize patients into low/high survival rate in a more reliable manner; (iii) edge biomarkers are significantly enriched in relevant biological functions or pathways, implying that the association changes in a network, rather than expression changes in individual molecules, tend to be causally related to cancer development. The new framework of edge biomarkers paves the way for diagnosing diseases and analyzing their molecular mechanisms by edges or networks in one-sample-for-one-individual basis. This also provides a powerful tool for precision medicine or big-data medicine. © The Author (2015). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.

  5. Single-molecule quantification of lipotoxic expression of activating transcription factor 3

    PubMed Central

    Wilson, Dennis W.; Rutledge, John C.

    2014-01-01

    Activating transcription factor 3 (ATF3) is a member of the mammalian activation transcription factor/cAMP, physiologically important in the regulation of pro- and anti-inflammatory target genes. We compared the induction of ATF3 protein as measured by Western blot analysis with single-molecule localization microscopy dSTORM to quantify the dynamics of accumulation of intranuclear ATF3 of triglyceride-rich (TGRL) lipolysis product-treated HAEC (Human Aortic Endothelial Cells). The ATF3 expression rate within the first three hours after treatment with TGRL lipolysis products is about 3500/h. After three hours we detected 33,090 ± 3,491 single-molecule localizations of ATF3. This was accompanied by significant structural changes in the F-actin network of the cells at ~3-fold increased localization precision compared to widefield microscopy after treatment. Additionally, we discovered a cluster size of approximately 384 nanometers of ATF3 molecules. We show for the first time the time course of ATF3 accumulation in the nucleus undergoing lipotoxic injury. Furthermore, we demonstrate ATF3 accumulation associated with increased concentrations of TGRL lipolysis products occurs in large aggregates. PMID:25189785

  6. Actin cytoskeleton and exocytosis in rat melanotrophs.

    PubMed

    Chowdhury, Helana H; Popoff, Michel R; Zorec, Robert

    2000-01-01

    We monitored secretory activity of single rat melanotrophs by the patch-clamp membrane capacitance measurements (C m ). Secretory activity was stimulated by cytosol dialysis with a patch-pipette solution containing 1μM [Ca 2+ ] i . Actin cytoskeleton was disaggregated by pretreating cells with Clostridium spiroforme toxin, which specifically ADP-ribosylates cellular actin. The extent of cytoskeleton disaggregation was monitored by phalloidin immunostaining. The maximal rate of secretion increases two folds in toxin-treated cells in comparison to controls, whereas the extent of calcium-induced secretory response was similar to that obtained in the non-treated cells. The results show that the subcortical actin network attenuates the rate of secretory activity, which we interpret to reflect a barrier function of cytoskeleton for exocytosis.

  7. Actin cytoskeleton and exocytosis in rat melanotrophs.

    PubMed

    Chowdhury, H H; Popoff, M R; Zorec, R

    2000-01-01

    We monitored secretory activity of single rat melanotrophs by the patch-clamp membrane capacitance measurements (Cm). Secretory activity was stimulated by cytosol dialysis with a patch-pipette solution containing 1 microM [Ca2+]i. Actin cytoskeleton was disaggregated by pretreating cells with Clostridium spiroforme toxin, which specifically ADP-ribosylates cellular actin. The extent of cytoskeleton disaggregation was monitored by phalloidin immunostaining. The maximal rate of secretion increases two folds in toxin-treated cells in comparison to controls, whereas the extent of calcium-induced secretory response was similar to that obtained in the non-treated cells. The results show that the subcortical actin network attenuates the rate of secretory activity, which we interpret to reflect a barrier function of cytoskeleton for exocytosis.

  8. Multi-Cellular Logistics of Collective Cell Migration

    PubMed Central

    Yamao, Masataka; Naoki, Honda; Ishii, Shin

    2011-01-01

    During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems. PMID:22205934

  9. Biophysical force regulation in 3D tumor cell invasion

    NASA Astrophysics Data System (ADS)

    Wu, Mingming

    When embedded within 3D extracellular matrices (ECM), animal cells constantly probe and adapt to the ECM locally (at cell length scale) and exert forces and communicate with other cells globally (up to 10 times of cell length). It is now well accepted that mechanical crosstalk between animal cells and their microenvironment critically regulate cell function such as migration, proliferation and differentiation. Disruption of the cell-ECM crosstalk is implicated in a number of pathologic processes including tumor progression and fibrosis. Central to the problem of cell-ECM crosstalk is the physical force that cells generate. By measuring single cell generated force within 3D collagen matrices, we revealed a mechanical crosstalk mechanism between the tumor cells and the ECM. Cells generate sufficient force to stiffen collagen fiber network, and stiffer matrix, in return promotes larger cell force generation. Our work highlights the importance of fibrous nonlinear elasticity in regulating tumor cell-ECM interaction, and results may have implications in the rapid tissue stiffening commonly found in tumor progression and fibrosis. This work is partially supported by NIH Grants R21RR025801 and R21GM103388.

  10. Identification of driving network of cellular differentiation from single sample time course gene expression data

    NASA Astrophysics Data System (ADS)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  11. Convergent evolution of gene networks by single-gene duplications in higher eukaryotes.

    PubMed

    Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

    2004-03-01

    By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix-loop-helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks emerging through single-gene duplications, the dominant importance of molecular modularity in the bottom-up construction of complex biological entities, and the convergent evolution of networks.

  12. Rapid cell-free forward engineering of novel genetic ring oscillators

    PubMed Central

    Niederholtmeyer, Henrike; Sun, Zachary Z; Hori, Yutaka; Yeung, Enoch; Verpoorte, Amanda; Murray, Richard M; Maerkl, Sebastian J

    2015-01-01

    While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the ‘repressilator’, a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hr. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior. DOI: http://dx.doi.org/10.7554/eLife.09771.001 PMID:26430766

  13. Efficient Assignment of Multiple E-MBMS Sessions towards LTE

    NASA Astrophysics Data System (ADS)

    Alexiou, Antonios; Bouras, Christos; Kokkinos, Vasileios

    One of the major prerequisites for Long Term Evolution (LTE) networks is the mass provision of multimedia services to mobile users. To this end, Evolved - Multimedia Broadcast/Multicast Service (E-MBMS) is envisaged to play an instrumental role during LTE standardization process and ensure LTE’s proliferation in mobile market. E-MBMS targets at the economic delivery, in terms of power and spectral efficiency, of multimedia data from a single source entity to multiple destinations. This paper proposes a novel mechanism for efficient radio bearer selection during E-MBMS transmissions in LTE networks. The proposed mechanism is based on the concept of transport channels combination in any cell of the network. Most significantly, the mechanism manages to efficiently deliver multiple E-MBMS sessions. The performance of the proposed mechanism is evaluated and compared with several radio bearer selection mechanisms in order to highlight the enhancements that it provides.

  14. Stochastic dynamics for idiotypic immune networks

    NASA Astrophysics Data System (ADS)

    Barra, Adriano; Agliari, Elena

    2010-12-01

    In this work we introduce and analyze the stochastic dynamics obeyed by a model of an immune network recently introduced by the authors. We develop Fokker-Planck equations for the single lymphocyte behavior and coarse grained Langevin schemes for the averaged clone behavior. After showing agreement with real systems (as a short path Jerne cascade), we suggest, both with analytical and numerical arguments, explanations for the generation of (metastable) memory cells, improvement of the secondary response (both in the quality and quantity) and bell shaped modulation against infections as a natural behavior. The whole emerges from the model without being postulated a-priori as it often occurs in second generation immune networks: so the aim of the work is to present some out-of-equilibrium features of this model and to highlight mechanisms which can replace a-priori assumptions in view of further detailed analysis in theoretical systemic immunology.

  15. Broken Detailed Balance of Filament Dynamics in Active Networks

    NASA Astrophysics Data System (ADS)

    Gladrow, J.; Fakhri, N.; MacKintosh, F. C.; Schmidt, C. F.; Broedersz, C. P.

    2016-06-01

    Myosin motor proteins drive vigorous steady-state fluctuations in the actin cytoskeleton of cells. Endogenous embedded semiflexible filaments such as microtubules, or added filaments such as single-walled carbon nanotubes are used as novel tools to noninvasively track equilibrium and nonequilibrium fluctuations in such biopolymer networks. Here, we analytically calculate shape fluctuations of semiflexible probe filaments in a viscoelastic environment, driven out of equilibrium by motor activity. Transverse bending fluctuations of the probe filaments can be decomposed into dynamic normal modes. We find that these modes no longer evolve independently under nonequilibrium driving. This effective mode coupling results in nonzero circulatory currents in a conformational phase space, reflecting a violation of detailed balance. We present predictions for the characteristic frequencies associated with these currents and investigate how the temporal signatures of motor activity determine mode correlations, which we find to be consistent with recent experiments on microtubules embedded in cytoskeletal networks.

  16. Rational Organization of Lanthanide-Based SMM Dimers into Three-Dimensional Networks.

    PubMed

    Yi, Xiaohui; Calvez, Guillaume; Daiguebonne, Carole; Guillou, Olivier; Bernot, Kevin

    2015-06-01

    Optimization of the reaction of [Ln(hfac)3]·2H2O and pyridine-N-oxide (PyNO), which is known to afford double-bridged dimers, leads to triple-bridged dimers of formula [(Ln(hfac)3)2(PyNO)3] (Ln = Gd (1), Dy (2)) from which the Dy derivative (2) behaves as a single-molecule magnet (SMM). The pseudo threefold axis symmetry of this zero-dimensional building block makes possible its extension into a tridimensional network. By changing PyNO for 4,4'-bipyridine N,N'-dioxide (4,4'BipyNO) a tridimensional compound of formula {[Ln(hfac)3]2(4,4'BipyNO)2]} (Ln = Eu (3), Gd (4), and Dy (5)) is then rationally obtained. This covalent three-dimensional (3D) network has a remarkably high cell volume (V = 24 419 A(3)) and is an arrangement of interpenetrated 3D subnetworks whose triple-bridged dimers still behave as SMMs.

  17. Mechanical Cell-Cell Communication in Fibrous Networks: The Importance of Network Geometry.

    PubMed

    Humphries, D L; Grogan, J A; Gaffney, E A

    2017-03-01

    Cells contracting in extracellular matrix (ECM) can transmit stress over long distances, communicating their position and orientation to cells many tens of micrometres away. Such phenomena are not observed when cells are seeded on substrates with linear elastic properties, such as polyacrylamide (PA) gel. The ability for fibrous substrates to support far reaching stress and strain fields has implications for many physiological processes, while the mechanical properties of ECM are central to several pathological processes, including tumour invasion and fibrosis. Theoretical models have investigated the properties of ECM in a variety of network geometries. However, the effects of network architecture on mechanical cell-cell communication have received little attention. This work investigates the effects of geometry on network mechanics, and thus the ability for cells to communicate mechanically through different networks. Cell-derived displacement fields are quantified for various network geometries while controlling for network topology, cross-link density and micromechanical properties. We find that the heterogeneity of response, fibre alignment, and substrate displacement fields are sensitive to network choice. Further, we show that certain geometries support mechanical communication over longer distances than others. As such, we predict that the choice of network geometry is important in fundamental modelling of cell-cell interactions in fibrous substrates, as well as in experimental settings, where mechanical signalling at the cellular scale plays an important role. This work thus informs the construction of theoretical models for substrate mechanics and experimental explorations of mechanical cell-cell communication.

  18. Photothermally triggered actuation of hybrid materials as a new platform for in vitro cell manipulation

    DOE PAGES

    Sutton, Amy; Shirman, Tanya; Timonen, Jaakko V. I.; ...

    2017-03-13

    Mechanical forces in the cell’s natural environment have a crucial impact on growth, differentiation and behaviour. Few areas of biology can be understood without taking into account how both individual cells and cell networks sense and transduce physical stresses. However, the field is currently held back by the limitations of the available methods to apply physiologically relevant stress profiles on cells, particularly with sub-cellular resolution, in controlled in vitro experiments. Here we report a new type of active cell culture material that allows highly localized, directional and reversible deformation of the cell growth substrate, with control at scales ranging frommore » the entire surface to the subcellular, and response times on the order of seconds. These capabilities are not matched by any other method, and this versatile material has the potential to bridge the performance gap between the existing single cell micro-manipulation and 2D cell sheet mechanical stimulation techniques.« less

  19. Photothermally triggered actuation of hybrid materials as a new platform for in vitro cell manipulation

    PubMed Central

    Sutton, Amy; Shirman, Tanya; Timonen, Jaakko V. I.; England, Grant T; Kim, Philseok; Kolle, Mathias; Ferrante, Thomas; Zarzar, Lauren D; Strong, Elizabeth; Aizenberg, Joanna

    2017-01-01

    Mechanical forces in the cell’s natural environment have a crucial impact on growth, differentiation and behaviour. Few areas of biology can be understood without taking into account how both individual cells and cell networks sense and transduce physical stresses. However, the field is currently held back by the limitations of the available methods to apply physiologically relevant stress profiles on cells, particularly with sub-cellular resolution, in controlled in vitro experiments. Here we report a new type of active cell culture material that allows highly localized, directional and reversible deformation of the cell growth substrate, with control at scales ranging from the entire surface to the subcellular, and response times on the order of seconds. These capabilities are not matched by any other method, and this versatile material has the potential to bridge the performance gap between the existing single cell micro-manipulation and 2D cell sheet mechanical stimulation techniques. PMID:28287116

  20. Photothermally triggered actuation of hybrid materials as a new platform for in vitro cell manipulation

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

    Sutton, Amy; Shirman, Tanya; Timonen, Jaakko V. I.

    Mechanical forces in the cell’s natural environment have a crucial impact on growth, differentiation and behaviour. Few areas of biology can be understood without taking into account how both individual cells and cell networks sense and transduce physical stresses. However, the field is currently held back by the limitations of the available methods to apply physiologically relevant stress profiles on cells, particularly with sub-cellular resolution, in controlled in vitro experiments. Here we report a new type of active cell culture material that allows highly localized, directional and reversible deformation of the cell growth substrate, with control at scales ranging frommore » the entire surface to the subcellular, and response times on the order of seconds. These capabilities are not matched by any other method, and this versatile material has the potential to bridge the performance gap between the existing single cell micro-manipulation and 2D cell sheet mechanical stimulation techniques.« less

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