Delivery of secreted placental alkaline phosphatase (SEAP) gene in vitro and in vivo as a component of recombinant avian adenovirus (CELO)

Recombinant adenoviruses capable of expressing the gene of secreted placentary alkaline phosphatase (SEAP) under control of CMV-promoter was obtained on the basis of CELO avian adenovirus and human adenovirus-5 (Ad5) genomes. The efficiency of the CELO vector was determined in experiments with transduction of human (293, A549, and H1299), mouse (B16), and avian (LMH) cell cultures. It was shown in C57BL/6 mice in vivo that SEAP gene is expressed under conditions of intravenous, intranasal, and intratumoral application of recombinant adenovirus CELO-SEAP. The duration of expression of the alkaline phosphatase CELO = SEAP gene in immunocompetent mouse body was 21 days. The level of SEAP gene expression was measured in the allantois fluid of chicken embryo infected with recombinant adenovirus CELO-SEAP.     

QSAR of multiple mutated antibodies

The aim of this study was to develop predictive quantitative structure-activity relationship (QSAR) modeling for antibody-peptide interactions. A small single chain antibody library was designed and manufactured around the murine anti-p24 (HIV-1) monoclonal antibody CB4-1 by use of statistical molecular design (SMD) principles and site directed mutagenesis, and its affinity for a p24 derived antigen was determined by fluorescence polarization. A satisfactory QSAR model (Q(2) = 0.74, R(2) = 0.88) was derived by correlating the affinity data to physicochemical property scales of the amino acids varied in the library. The model explains most of the antibody-antigen interactions of the studied set, and provides insights into the molecular mechanism involved in antigen binding.     

High Levels of Genetic Diversity in Salix viminalis of the Czech Republic as Revealed by Microsatellite Markers

Willows (Salix spp.) grown as short rotation coppice are recognised as an important bioenergy crop, and breeding programmes are underway in several countries, including the Czech Republic. The basket willow Salix viminalis is one of the few willow species that is widespread in the Czech Republic and thus a potential source of diversity, but the most extensive germplasm collection available shows evidence of redundancy. To investigate levels of variation in natural populations of this species for use in crop improvement programmes, a set of 38 microsatellite markers was used to assess genetic diversity and population structure among 84 S. viminalis individuals collected from seven Czech rivers (the Odra, Be?va, Morava, Dyje, Jihlava, Sázava and Vltava), covering a wide geographic distribution. The markers detected 6.95 alleles per locus on average with 92?% of the sampled individuals having a unique multilocus genotype giving a high clonal richness measure among all samples (R?=?0.952). Three sets of putative clones (with identical genotypes as determined by the markers used here) were also identified. Significant levels of genetic diversity were revealed within all sampling sites. With the exception of sites on the Odra and Morava, pairwise F _ST (0.02?C0.1) values indicated moderate differentiation between sites. Principal coordinates analysis revealed some separation of the Dyje individuals from all others. This was in agreement with the population structure results derived from Bayesian analyses using STRUCTURE software. These results provide the first evidence that potentially useful levels of genotypic variation are present within natural S. viminalis populations in the Czech Republic.     

Genetic Improvement of Willow for Bioenergy and Biofuels

Willows (Salix spp.) are a very diverse group of catkin-bearing trees and shrubs that are widely distributed across temperate regions of the globe.Some species respond well to being grown in short rotation coppice (SRC) cycles,which are much shorter than conventional forestry.Coppicing reinvigorates growth and the biomass rapidly accumulated can be used as a source of renewable carbon for bioenergy and biofuels.As SRC willows re-distribute nutrients during the perennial cycle they require only minimal nitro...     

Cultivation of reaggregated brain cells in rapidly rotating mini-rollers

An original method of cultivation of reaggregated brain cells with the aid of high-speed portable mini-rollers is described. The mini-roller consists of parallel rollers and an electric motor rotating the flasks at a speed of 60 to 70 rpm. The Moscona technique was used for preparing brain cell suspensions. During cultivation of the suspension of dissociated cells in high-speed mini-rollers, reaggregates with an internal organotypic structure were obtained. The method suggested provides stable and reproducible results.     

Scalable and flexible inference framework for stochastic dynamic single-cell models

Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cellular processes and to rationalise cell-to-cell variability within the population. However, extracting mechanistic information from single-cell data has proven difficult. This requires statistical methods to infer unknown model parameters from dynamic, multi-individual data accounting for heterogeneity caused by both intrinsic (e.g. variations in chemical reactions) and extrinsic (e.g. variability in protein concentrations) noise. Although several inference methods exist, the availability of efficient, general and accessible methods that facilitate modelling of single-cell data, remains lacking. Here we present a scalable and flexible framework for Bayesian inference in state-space mixed-effects single-cell models with stochastic dynamic. Our approach infers model parameters when intrinsic noise is modelled by either exact or approximate stochastic simulators, and when extrinsic noise is modelled by either time-varying, or time-constant parameters that vary between cells. We demonstrate the relevance of our approach by studying how cell-to-cell variation in carbon source utilisation affects heterogeneity in the budding yeast Saccharomyces cerevisiae SNF1 nutrient sensing pathway. We identify hexokinase activity as a source of extrinsic noise and deduce that sugar availability dictates cell-to-cell variability.