Search

Chronic cytomegalovirus (CMV) infection leads to long-term maintenance of extraordinarily large CMV-specific T cell populations. The magnitude of this so-called ‘memory inflation’ is thought to mainly depend on antigenic stimulation during the chronic phase of infection. However, by mapping the long-term development of CD8+ T cell families derived from single naive precursors, we find that fate decisions made during the acute phase of murine CMV infection can alter the level of memory inflation by more than 1,000-fold. Counterintuitively, a T cell family’s capacity for memory inflation is not determined by its initial expansion. Instead, those rare T cell families that dominate the chronic phase of infection show an early transcriptomic signature akin to that of established T central memory cells. Accordingly, a T cell family’s long-term dominance is best predicted by its early content of T central memory precursors, which later serve as a stem-cell-like source for memory inflation. T cell memory formation is often described as occurring during the chronic phases of infection. Buchholz and colleagues use the phenomenon of ‘memory inflation’ following cytomegalovirus infection to show that a tiny subset of self-renewing T cells branch off early from the bulk population to generate memory.

Rapid clonal expansion of antigen specific T cells is a fundamental feature of adaptive immune responses. It enables the outgrowth of an individual T cell into thousands of clonal descendants that diversify into short-lived effectors and long-lived memory cells. Clonal expansion is thought to be programmed upon priming of a single naïve T cell and then executed by homogenously fast divisions of all of its descendants. However, the actual speed of cell divisions in such an emerging ‘T cell family’ has never been measured with single-cell resolution. Here, we utilize continuous live-cell imagingin vitroto track the division speed and genealogical connections of all descendants derived from a single naïve CD8+T cell throughout up to ten divisions of activation-induced proliferation. This comprehensive mapping of T cell family trees identifies a short burst phase, in which division speed is homogenously fast and maintained independent of external cytokine availability or continued T cell receptor stimulation. Thereafter, however, division speed diversifies and model-based computational analysis using a novel Bayesian inference framework for tree-structured data reveals a segregation into heritably fast and slow dividing branches. This diversification of division speed is preceded already during the burst phase by variable expression of the interleukin-2 receptor alpha chain. Later it is accompanied by selective expression of memory marker CD62L in slower dividing branches. Taken together, these data demonstrate that T cell clonal expansion is structured into subsequent burst and diversification phases the latter of which coincides with specification of memory vs. effector fate.SignificanceRapid clonal expansion of antigen-specific T cells is a fundamental feature of adaptive immune responses. Here, we utilize continuous live-cell imagingin vitroto track the division speed and genealogical connections of all descendants derived from a single naïve CD8+T cell throughout up to ten divisions of activation-induced proliferation. Bayesian inference of tree-structured data reveals that clonal expansion is divided into a homogenously fast burst phase encompassing two to three divisions and a subsequent diversification phase during which T cells segregate into quickly dividing effector T cells and more slowly cycling memory precursors. Our work highlights cell cycle speed as a major heritable property that is regulated in parallel to key lineage decisions of activated T cells.

Chronic cytomegalovirus (CMV) infection leads to long-term maintenance of extraordinarily large CMV-specific T cell populations. The magnitude of this so-called 'memory inflation' is thought to mainly depend on antigenic stimulation during the chronic phase of infection. However, by mapping the long-term development of CD8

Background: Chrysanthemum; also commonly known as mums or chrysanths, is one of the most important ornamental crops worldwide. Introducing desirable traits into this valuable plant by the conventional breeding has so far been faced with some restrictions due to the limited gene pool and cross-incompatibility. Therefore, breeders have decided to exploit Agrobacterium-mediated transformation methods in order to satisfy the growing market demands. However, more efficient in vitro regeneration protocols are required for this approach.Objectives: The objective of this research was to develop an efficient protocol for an in vitro plant regeneration by the examining the effects of various combinations and concentrations of the plant growth regulators (PGRs) and different explants types.Materials and Methods: The leaf and petiole explants of the Chrysanthemum morifolium cv. ‘Resomee Splendid’ were collected from the in vitro grown plantlets. Murashige and Skooge (MS) medium was supplemented with different concentrations and combinations of benzylaminopurine (BAP), 1-naphthaleneacetic acid (NAA) and thidiazuron (TDZ). Thereafter, the effects of these hormonal treatments were investigated on shoot initiation percentage, the average number of shoots per explants, callogenesis, and the type of organogenesis in regard to both types of the explants.Results: Shoots were directly formed from leaf explants on the media that only contained BAP without callus formation. Amongst the other hormonal treatments, a combination of 4.5 mg.L-1 BAP plus 1 mg.L-1 NAA resulted in the direct organogenesis from the leaf explants, which was superior to the other combinations and concentrations. In regard to the petiole explants, direct shoot formation occurred in all the media except for the ones which were fortified with TDZ. In this case, considering the shoot initiation percentage and the mean shoot number per explants, the best results were achieved in the medium supplemented with 1.5 mg.L-1 BAP and 1 mg.L-1 NAA. Results showed that interaction of either BAP or TDZ with NAA was necessary for the callus induction.Conclusions: Significant differences in shoot initiation percentage and the average number of shoots per explants were observed both in leaves and petioles grown on different media. Moreover, the callogenesis rates, as well as organogenesis types, showed some differences among the studied explants when compared on the same media.

This thesis aims to establish robust, reliable and feasible mesoscopic approximative methods that can be used in the formalism of systems biology to learn about the underlying mechanisms of stochastic biochemical processes. One of the main contributions of this work is proposing a model reduction, based on the topological structure of the reaction network, that enables mesoscopic modelling of large-scale biological processes. In addition, a simulation platform was developed as a part of this thesis which enables efficient simulation and comprehensive comparisons across a broad range of modelling approaches. Ziel dieser Dissertation ist es, zugleich robuste, zuverlässige und realisierbare mesoskopische Näherungsverfahren zu schaffen. Diese können auf biochemische Systeme angewendet werden, um mehr über ihre stochastische Natur zu lernen. Einer der Hauptbeiträge dieser Arbeit ist die Ausarbeitung einer Modell-Reduktion, die auf der topologischen Struktur des Reaktionsnetzwerks basiert. Sie ermöglicht eine mesoskopische Modellierung von umfangreichen biologischen Prozessen. Des Weiteren wurde eine Simulations-Plattform als Teil dieser Arbeit entwickelt, die numerisch-effiziente Rechnungen gewährleistet und umfassende Vergleiche zwischen verschiedenen Modellierungsansätzen ermöglicht.

The performance of poly(arylene ether sulfone) as a proton exchange membrane, for application in a fuel cell, such as carboxylic acid side chain effects on the structural and dynamical properties have been studied by molecular dynamics simulation at 353 K. Different percentage of carboxylated monomer were simulated and the radial distribution function, water cluster size and mean square displacement were evaluated. The results showed that monomer carboxylation up to 10%, decreased the conductivity according to vehicular mechanism and then at 15% of monomer carboxylation the conductivity increased. Also, the greatest water clusters were formed at 15% carboxylated monomer and the increase in acidic sites made the polymer more hydrophilic. In addition, the diffusion and solubility of the gases, O 2 and H 2 , into the membrane were studied and the results indicated that H 2 has a higher diffusion coefficient than O 2 and the diffusion phenomenon has a determining effect on the performance of proton exchange membrane.

The time-evolution of continuous-time discrete-state biochemical processes is governed by the Chemical Master Equation (CME), which describes the probability of the molecular counts of each chemical species. As the corresponding number of discrete states is, for most processes, large, a direct numerical simulation of the CME is in general infeasible. In this paper we introduce the method of conditional moments (MCM), a novel approximation method for the solution of the CME. The MCM employs a discrete stochastic description for low-copy number species and a moment-based description for medium/high-copy number species. The moments of the medium/high-copy number species are conditioned on the state of the low abundance species, which allows us to capture complex correlation structures arising, e.g., for multi-attractor and oscillatory systems. We prove that the MCM provides a generalization of previous approximations of the CME based on hybrid modeling and moment-based methods. Furthermore, it improves upon these existing methods, as we illustrate using a model for the dynamics of stochastic single-gene expression. This application example shows that due to the more general structure, the MCM allows for the approximation of multi-modal distributions.

Motivation Stochastic molecular processes are a leading cause of cell-to-cell variability. Their dynamics are often described by continuous-time discrete-state Markov chains and simulated using stochastic simulation algorithms. As these stochastic simulations are computationally demanding, ordinary differential equation models for the dynamics of the statistical moments have been developed. The number of state variables of these approximating models, however, grows at least quadratically with the number of biochemical species. This limits their application to small- and medium-sized processes. Results In this article, we present a scalable moment-closure approximation (sMA) for the simulation of statistical moments of large-scale stochastic processes. The sMA exploits the structure of the biochemical reaction network to reduce the covariance matrix. We prove that sMA yields approximating models whose number of state variables depends predominantly on local properties, i.e. the average node degree of the reaction network, instead of the overall network size. The resulting complexity reduction is assessed by studying a range of medium- and large-scale biochemical reaction networks. To evaluate the approximation accuracy and the improvement in computational efficiency, we study models for JAK2/STAT5 signalling and NFκB signalling. Our method is applicable to generic biochemical reaction networks and we provide an implementation, including an SBML interface, which renders the sMA easily accessible. Availability and implementation The sMA is implemented in the open-source MATLAB toolbox CERENA and is available from https://github.com/CERENADevelopers/CERENA. Supplementary information Supplementary data are available at Bioinformatics online.

Quantitative mechanistic models are valuable tools for disentangling biochemical pathways and for achieving a comprehensive understanding of biological systems. However, to be quantitative the parameters of these models have to be estimated from experimental data. In the presence of significant stochastic fluctuations this is a challenging task as stochastic simulations are usually too time-consuming and a macroscopic description using reaction rate equations (RREs) is no longer accurate. In this manuscript, we therefore consider moment-closure approximation (MA) and the system size expansion (SSE), which approximate the statistical moments of stochastic processes and tend to be more precise than macroscopic descriptions. We introduce gradient-based parameter optimization methods and uncertainty analysis methods for MA and SSE. Efficiency and reliability of the methods are assessed using simulation examples as well as by an application to data for Epo-induced JAK/STAT signaling. The application revealed that even if merely population-average data are available, MA and SSE improve parameter identifiability in comparison to RRE. Furthermore, the simulation examples revealed that the resulting estimates are more reliable for an intermediate volume regime. In this regime the estimation error is reduced and we propose methods to determine the regime boundaries. These results illustrate that inference using MA and SSE is feasible and possesses a high sensitivity., Author Summary In this manuscript, we introduce efficient methods for parameter estimation for stochastic processes. The stochasticity of chemical reactions can influence the average behavior of the considered system. For some biological systems, a microscopic, stochastic description is computationally intractable but a macroscopic, deterministic description too inaccurate. This inaccuracy manifests itself in an error in parameter estimates, which impede the predictive power of the proposed model. Until now, no rigorous analysis on the magnitude of the estimation error exists. We show by means of two simulation examples that using mesoscopic descriptions based on the system size expansions and moment-closure approximations can reduce this estimation error compared to inference using a macroscopic description. This reduction is most pronounced in an intermediate volume regime where the influence of stochasticity on the average behavior is moderately strong. For the JAK/STAT pathway where experimental data is available, we show that one parameter that was not structurally identifiable when using a macroscopic description becomes structurally identifiable when using a mesoscopic description for parameter estimation.

The miR-302 family is one of the main groups of microRNAs, which are highly expressed in embryonic stem cells (ESCs). Previous reports have indicated that miR-302 can reduce the proliferation rate of some cancer cells while compromising on their oncogenic potential at the same time without having the same effect on normal somatic cells. In this study we aimed to further investigate the role of the miR-302 cluster in multiple cancer signaling pathways using A-375 melanoma and HT-29 colorectal cancer cells. Our results indicate that the miR-302 cluster has the potential to modulate oncogenic properties of cancer cells through inhibition of proliferation, angiogenesis and invasion, and through reversal of the epithelial-to-mesenchymal transition (EMT) in these cells. We showed for the first time that overexpression of miR-302 cluster sensitized A-375 and HT-29 cells to hypoxia and also to the selective BRAF inhibitor vemurafenib. MiR-302 is a pleiotropically acting miRNA family which may have significant implications in controlling cancer progression and invasion. It acts through a reprogramming process, which has a global effect on a multitude of cellular pathways and events. We propose that reprogramming of cancer cells by epigenetic factors, especially miRNAs might provide an efficient tool for controlling cancer and especially for those with more invasive nature.

The authors report femtosecond pump-probe measurements of electronic energy relaxation in conventional metallic and high-T/sub c/ oxide superconductors. In conventional metallic superconductors, the energy relaxation rate of electrons is used to determine the electron-phonon coupling constant lambda . The agreement between the lambda values measured and those obtained by other techniques is excellent, confirming the theoretical predictions of P.B. Allen (1987). A novel Cu overlayer technique was developed in order to measure certain metals which do not have a strong optical transition to states near the Fermi level at a laser energy, of 1.98 eV. The effect of different Cu overlayer thicknesses has been studied. In the new copper-oxide high-T/sub c/ superconducting materials, electronic energy relaxation is monitored by measuring changes epsilon /sub 2/. The observed changes in epsilon /sub 2/ are related to the dynamics of the Cu d to O p band charge transfer excitation occurring in the CuO/sub 2/ planes. By depleting a YBa/sub 2/Cu/sub 3/O/sub 7- delta / sample of oxygen, one can simultaneously vary the Fermi level and the T/sub c/ and make dramatic changes in the pump-probe signal. An estimate of lambda , in several high-T/sub c/ materials, is also made using Allen's theory to fit the relaxation behavior of epsilon /sub 2/.

We present the first femtosecond pump-prove measurements of the room temperature optical properties of high-Tc superconductors. Three oriented superconducting thin-films were studied: YBa2Cu3O7−δ, Bi2Sr2CaCu2O8+z, and Bi2Sr2Ca2Cu3O10+y. The observed changes in e2 can be related to the dynamics of the Cu d to O p band charge transfer excitation occurring in the Cu  O planes. By depleting the YBa2Cu3O7−δ sample of oxygen, we simultaneously vary the Fermi level and the Tc. The sign of Δe2 is found to depend on the Fermi level position, while the recovery time is found to increase markedly with decreasing Tc.

We report time domain observations of coherent lattice vibrations in bismuth and antimony. Phonons are impulsively generated, and detected through reflectivity modulation with 70 fs pulses of laser light at 1.98 eV. With this technique, we demonstrate that coherent lattice oscillations can be studied by reflection in opaque materials, but with selection rules which may differ from conventional impulsive stimulated Raman scattering.

Abstract 2558 Background: The increasing use in the clinic of genome-wide analyses has placed a greater burden on, and need for novel informatics tools. Ideally such tools should be capable of reducing the vast amount of information generated per patient into integrated, simplified, intuitive, and preferably, visual data that can be easily translated into diagnostic, prognostic and theranostic actionable information. With the overarching goal of clarity and user-friendliness in mind we have co-opted a genome-wide representational tool used widely in non-clinical discovery genomics and tailored it to achieve its intended clinical use, i.e. simple graphical representation of complex data enabling clinicians to quickly derive meaning from robust clinical laboratory modalities, such as next-generation sequencing technologies and next-gen microarrays. Materials & Methods: For a proof of concept rendition, we collected cytogenetics, array CGH, and gene expression data on a subset of well-characterized core binding factor positive leukemias. Leukemias containing CBFA2 [t(8;21)(q22;q22)] or CBFB [inv(16)(p13q22)] fusion proteins were included in the study. Gene expression profiling data sets were extracted from Stanford Microarray Database. The associated karyotypes were obtained from the linked PubMed papers and directly from the authors. aCGH data sets were extracted from the SKY/M-FISH and CGH database at NCBI. All datasets for each case of CBF+ leukemia represented in this study were unified into a Microsoft Access Database, which contained the numeric coordinates of all genes included, and their associated cytogenetic band position. Results: By subjecting the data to customized subroutines, it was possible to extract and display relevant subsets of data into a customizable visually intuitive display, which allowed naïve observers to quickly assimilate all the clinically relevant genetic information on a particular AML case. From such a representation, heat maps of subsets of genes, structural and numerical chromosome abnormalities, copy-number changes and subsets of relevant point mutations could be displayed, all in a single integrated genome anchored image. Discussion: Our graphic user interface displays positionally-anchored genome-wide data and could be customized to represent CNVs, miRNA expression and DNA methylation patterns, associated phenotypes, etc, in addition to those shown in this study. Furthermore, any of these parameters can be segmented into functionally related groups to display, for instance, regulators of transcription, cell lineage or differentiation, proliferation, apoptosis, DNA repair, expression of genes that govern response or sensitivity to chemotherapy or entire signaling pathways. Conclusion: Integrated graphical representation of relevant genome-wide data facilitates and harmonizes communication among physicians with different expertise and facilitates patient stratification into defined risk groups, which is critically important in enabling risk-adapted and/or targeted therapies. Disclosures: No relevant conflicts of interest to declare.

We report the first systematic femtosecond pump-probe measurements of the electron-phonon coupling constant \ensuremath{\lambda} in thin films of Cu, Au, Cr, Ti, W, Nb, V, Pb, NbN, and ${\mathrm{V}}_{3}$Ga. The agreement between our measured \ensuremath{\lambda} values and those obtained by other techniques is excellent, thus confirming recent theoretical predictions of Allen. By depositing thin Cu overlayers when necessary, we can extend this technique to nearly any metallic thin film.

The Elishberg generalization of BCS theory includes a parameter λ describing the strength of the electron - phonon coupling constant.1 In 1987, P. B. Allen made the suggestion that λ might be measured in the metallic superconductors using femtosecond thermomodulation (pump - probe) spectroscopy.2 Such experiments3,4 have been performed on Cu and Au, although not in the context of measuring λ. Here we report the results of systematic femtosecond thermomodulation measurements of λ in metallic thin films of Cu, Au, Cr, Ti, W, Nb, V, Pb, NbN, and V3Ga. The agreement between our measured λ values and those obtained by other means is excellent, thus confirming Allen’s theory. This method to measure λ has several advantages over other techniques: it is the most direct measure of λ〈ω2〉, it works at room temperature, it can be applied to both superconducting and non-superconducting samples, and it is not affected by interactions competing with superconductivity such as the antiferromagnetism in Cr.