Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Identification of Nucleic Acid Binding Sites on Translin-Associated Factor X (TRAX) Protein

Translin and TRAX proteins play roles in very important cellular processes such as DNA recombination, spatial and temporal expression of mRNA, and in siRNA processing. Translin forms a homomeric nucleic acid binding complex and binds to ssDNA and RNA. However, a mutant translin construct that forms homomeric complex lacking nucleic acid binding activity is able to form fully active heteromeric translin-TRAX complex when co-expressed with TRAX. A substantial progress has been made in identifying translin sites that mediate its binding activity, while TRAX was thought not to bind DNA or RNA on its own. We here for the first time demonstrate nucleic acid binding to TRAX by crosslinking radiolabeled ssDNA to heteromeric translin-TRAX complex using UV-laser. The TRAX and translin, photochemically crosslinked with ssDNA, were individually detected on SDS-PAGE. We mutated two motifs in TRAX and translin, designated B2 and B3, to help define the nucleic acid binding sites in the TRAX sequence. The most pronounced effect was observed in the mutants of B3 motif that impaired nucleic acid binding activity of the heteromeric complexes. We suggest that both translin and TRAX are binding competent and contribute to the nucleic acid binding activity

Planning for the next influenza H1N1 season: a modelling study

<p>Abstract</p> <p>Background</p> <p>The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge.</p> <p>Methods</p> <p>This was a modelling study based on data on medical visits for influenza-like illness collected by the French General Practitioner Sentinel network, as well as pandemic H1N1 vaccination coverage rates, and an individual-centred model devoted to influenza. We estimated infection attack rates during the first 2009 pandemic H1N1 season in France, and the rates of pre- and post-exposure immunity. We then simulated various scenarios in which a pandemic influenza H1N1 virus would be reintroduced into a population with varying levels of protective cross-immunity, and considered the impact of extending influenza vaccination.</p> <p>Results</p> <p>During the first pandemic season in France, the proportion of infected persons was 18.1% overall, 38.3% among children, 14.8% among younger adults and 1.6% among the elderly. The rates of pre-exposure immunity required to fit data collected during the first pandemic season were 36% in younger adults and 85% in the elderly. We estimated that the rate of post-exposure immunity was 57.3% (95% Confidence Interval (95%CI) 49.6%-65.0%) overall, 44.6% (95%CI 35.5%-53.6%) in children, 53.8% (95%CI 44.5%-63.1%) in younger adults, and 87.4% (95%CI 82.0%-92.8%) in the elderly.</p> <p>The shape of a second season would depend on the degree of persistent protective cross-immunity to descendants of the 2009 H1N1 viruses. A cross-protection rate of 70% would imply that only a small proportion of the population would be affected. With a cross-protection rate of 50%, the second season would have a disease burden similar to the first, while vaccination of 50% of the entire population, in addition to the population vaccinated during the first pandemic season, would halve this burden. With a cross-protection rate of 30%, the second season could be more substantial, and vaccination would not provide a significant benefit.</p> <p>Conclusions</p> <p>These model-based findings should help to prepare for a second pandemic season, and highlight the need for studies of the different components of immune protection.</p

Modeling of negative Poisson’s ratio (auxetic) crystalline cellulose Iβ

Energy minimizations for unstretched and stretched cellulose models using an all-atom empirical force field (Molecular Mechanics) have been performed to investigate the mechanism for auxetic (negative Poisson’s ratio) response in crystalline cellulose Iβ from kraft cooked Norway spruce. An initial investigation to identify an appropriate force field led to a study of the structure and elastic constants from models employing the CVFF force field. Negative values of on-axis Poisson’s ratios nu31 and nu13 in the x1-x3 plane containing the chain direction (x3) were realized in energy minimizations employing a stress perpendicular to the hydrogen-bonded cellobiose sheets to simulate swelling in this direction due to the kraft cooking process. Energy minimizations of structural evolution due to stretching along the x3 chain direction of the ‘swollen’ (kraft cooked) model identified chain rotation about the chain axis combined with inextensible secondary bonds as the most likely mechanism for auxetic response

Survivability in Hostile Environments

This paper introduces a novel ERP strategic design model of survivability using natural analogies. Management theories frequently emerge from biological metaphors. Every entity seeks to continue existence, to survive. Firms, governments and individuals balance survivability factors of efficiency, resilience, and prominence (ERP) to stay alive. Researchers employ a comparative analysis methodology between squids, military ships, startup firms in the defense industry and strategic supply chains using these analogies and novel ERP model as an analytical framework. Comparing the cases yields general principles of strategic design that potentially extend to other entities that function in hostile environments. These principles primarily relate to the relative significance of threats, the importance of ERP factors, the nature of interrelationships among the ERP factors, and the tradeoffs involved while taking actions to improve survivability. The paper offers insights into the use of ERP analogical case analysis as a means for interdependent entities to co-create strategies to plan for and overcome dilemmas in hostile environments

Electronic and magnetic properties of graphite quantum dots

We study the electronic and magnetic properties of multilayer quantum dots (MQDs) of graphite in the nearest-neighbor approximation of tight-binding model. We calculate the electronic density of states and orbital susceptibility of the system as function of the Fermi level location. We demonstrate that properties of MQD depend strongly on the shape of the system, on the parity of the layer number and on the form of the cluster edge. The special emphasis is given to reveal the new properties with respect to the monolayer quantum dots of graphene. The most interesting results are obtained for the triangular MQD with zig-zag edge at near-zero energies. The asymmetrically smeared multi-peak feature is observed at Dirac point within the size-quantized energy gap region, where monolayer graphene flakes demonstrate the highly-degenerate zero-energy state. This feature, provided by the edge-localized electronic states results in the splash-wavelet behavior in diamagnetic orbital susceptibility as function of energy

Extracting fluorescent reporter time courses of cell lineages from high-throughput microscopy at low temporal resolution

The extraction of fluorescence time course data is a major bottleneck in high-throughput live-cell microscopy. Here we present an extendible framework based on the open-source image analysis software ImageJ, which aims in particular at analyzing the expression of fluorescent reporters through cell divisions. The ability to track individual cell lineages is essential for the analysis of gene regulatory factors involved in the control of cell fate and identity decisions. In our approach, cell nuclei are identified using Hoechst, and a characteristic drop in Hoechst fluorescence helps to detect dividing cells. We first compare the efficiency and accuracy of different segmentation methods and then present a statistical scoring algorithm for cell tracking, which draws on the combination of various features, such as nuclear intensity, area or shape, and importantly, dynamic changes thereof. Principal component analysis is used to determine the most significant features, and a global parameter search is performed to determine the weighting of individual features. Our algorithm has been optimized to cope with large cell movements, and we were able to semi-automatically extract cell trajectories across three cell generations. Based on the MTrackJ plugin for ImageJ, we have developed tools to efficiently validate tracks and manually correct them by connecting broken trajectories and reassigning falsely connected cell positions. A gold standard consisting of two time-series with 15,000 validated positions will be released as a valuable resource for benchmarking. We demonstrate how our method can be applied to analyze fluorescence distributions generated from mouse stem cells transfected with reporter constructs containing transcriptional control elements of the Msx1 gene, a regulator of pluripotency, in mother and daughter cells. Furthermore, we show by tracking zebrafish PAC2 cells expressing FUCCI cell cycle markers, our framework can be easily adapted to different cell types and fluorescent markers

Dynamic analysis of stochastic transcription cycles

In individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using new mathematical tools that allowed us to reconstruct dynamic transcription rates of different reporter genes controlled by identical promoters in the same living cell. Quantitative microscopic analysis of two reporter genes, firefly luciferase and destabilized EGFP, was used to analyze the dynamics of prolactin promoter-directed gene expression in living individual clonal and primary pituitary cells over periods of up to 25 h. We quantified the time-dependence and cyclicity of the transcription pulses and estimated the length and variation of active and inactive transcription phases. We showed an average cycle period of approximately 11 h and demonstrated that while the measured time distribution of active phases agreed with commonly accepted models of transcription, the inactive phases were differently distributed and showed strong memory, with a refractory period of transcriptional inactivation close to 3 h. Cycles in transcription occurred at two distinct prolactin-promoter controlled reporter genes in the same individual clonal or primary cells. However, the timing of the cycles was independent and out-of-phase. For the first time, we have analyzed transcription dynamics from two equivalent loci in real-time in single cells. In unstimulated conditions, cells showed independent transcription dynamics at each locus. A key result from these analyses was the evidence for a minimum refractory period in the inactive-phase of transcription. The response to acute signals and the result of manipulation of histone acetylation was consistent with the hypothesis that this refractory period corresponded to a phase of chromatin remodeling which significantly increased the cyclicity. Stochastically timed bursts of transcription in an apparently random subset of cells in a tissue may thus produce an overall coordinated but heterogeneous phenotype capable of acute responses to stimuli