The 5′ Flanking Region and Intron1 of the Bovine Prion Protein Gene (PRNP) Are Responsible for Negative Feedback Regulation of the Prion Protein

Transcription factors regulate gene expression by controlling the transcription rate. Some genes can repress their own expression to prevent over production of the corresponding protein, although the mechanism and significance of this negative feedback regulation remains unclear. In the present study, we describe negative feedback regulation of the bovine prion protein (PrP) gene PRNP in Japanese Black cattle. The PrP-expressing plasmid pEF-boPrP and luciferase-expressing plasmids containing the partial promoter fragment of PRNP incorporating naturally occurring single-nucleotide or insertion/deletion polymorphisms were transfected into N2a cells. Transfection of pEF-boPrP induced PrP overexpression and decreased the promoter activity of PRNP in the wild-type haplotype (23-bp Del, 12-bp Del, and −47C). Reporter gene assays further demonstrated that the 12- and 23-bp Ins/Del polymorphisms, which are thought to be associated with Sp1 (Specific protein 1) and RP58 (Repressor Protein with a predicted molecular mass of 58 kDa), in intron1 and the upstream region, respectively, and an additional polymorphism (−47C→A) in the Sp1-binding site responded differently to PrP overexpression. With the −47C SNP, the presence of the Del in either the 23-bp Ins/Del or the 12-bp Ins/Del allele was essential for the negative feedback caused by PrP overexpression. Furthermore, deletion mutants derived from the wild-type haplotype showed that nucleotides −315 to +2526, which include the 5′-flanking region and exon1, were essential for the response. These results indicate that certain negative feedback response elements are located in these sequences, suggesting that regulation by transcription factors such as Sp1 and RP58 may contribute to the negative feedback mechanism of PRNP

Nontrivial dependence of dielectric stiffness and SHG on dc bias in relaxors and dipole glasses

Dielectric permittivity and Second Harmonic Generation (SHG) studies in the field-cooled mode show a linear dependence of dielectric stiffness (inverse dielectric permittivity) on dc bias in PMN-PT crystals and SHG intensity in KTaO$_{3}$:Li at small Li concentrations. We explain this unusual result in the framework of a theory of transverse, hydrodynamic-type, instability of local polarization.Comment: 5 figure

A spectroscopy approach to the study of virus infection in the endophytic fungus Epichloë festucae

<p>Abstract</p> <p>Background</p> <p>In this work we propose a rapid method based on visible and near-infrared (Vis-NIR) spectroscopy to determine the occurrence of double-stranded RNA (dsRNA) viruses in <it>Epichloë festucae </it>strains isolated from <it>Festuca rubra </it>plants. In addition, we examined the incidence of infections by <it>E. festucae </it>in populations of <it>F. rubra </it>collected in natural grasslands of Western Spain.</p> <p>Methods</p> <p>Vis-NIR spectra (400-2498 nm) from 124 virus-infected and virus-free <it>E. festucae </it>isolates were recorded directly from ground and freeze-dried mycelium. To estimate how well the spectra for uninfected and infected fungal samples could be differentiated, we used partial least-squares discriminant analysis (PLS1-DA) and several data pre-treatments to develop calibration models.</p> <p>Results</p> <p>Applying the best regression model, obtained with two sampling years and using standard normal variate (SNV) combined with first derivative transformation to a new validating data set (42 samples), we obtained a correct classification for 75% of the uninfected isolates and up to 86% of the infected isolates.</p> <p>Conclusions</p> <p>The results obtained suggest that Vis-NIR spectroscopy is a promising technology for detection of viral infections in fungal samples when an alternative faster approach is desirable. It provides a tool adequately exact and more time- and cost-saving than the conventional reference analysis.</p

Protein Structure along the Order–Disorder Continuum

Thermal fluctuations cause proteins to adopt an ensemble of conformations wherein the relative stability of the different ensemble members is determined by the topography of the underlying energy landscape. “Folded” proteins have relatively homogeneous ensembles, while “unfolded” proteins have heterogeneous ensembles. Hence, the labels “folded” and “unfolded” represent attempts to provide a qualitative characterization of the extent of structural heterogeneity within the underlying ensemble. In this work, we introduce an information-theoretic order parameter to quantify this conformational heterogeneity. We demonstrate that this order parameter can be estimated in a straightforward manner from an ensemble and is applicable to both unfolded and folded proteins. In addition, a simple formula for approximating the order parameter directly from crystallographic B factors is presented. By applying these metrics to a large sample of proteins, we show that proteins span the full range of the order–disorder axis.National Institutes of Health (U.S.) (NIH Grant 5R21NS063185-02

Comparison of gene expression during in vivo and in vitro postnatal retina development

Retina explants are widely used as a model of neural development. To define the molecular basis of differences between the development of retina in vivo and in vitro during the early postnatal period, we carried out a series of microarray comparisons using mouse retinas. About 75% of 8,880 expressed genes from retina explants kept the same expression volume and pattern as the retina in vivo. Fewer than 6% of the total gene population was changed at two consecutive time points, and only about 1% genes showed more than a threefold change at any time point studied. Functional Gene Ontology (GO) mapping for both changed and unchanged genes showed similar distribution patterns, except that more genes were changed in the GO clusters of response to stimuli and carbohydrate metabolism. Three distinct expression patterns of genes preferentially expressed in rod photoreceptors were observed in the retina explants. Some genes showed a lag in increased expression, some showed no change, and some continued to have a reduced level of expression. An early downregulation of cyclin D1 in the explanted retina might explain the reduction in numbers of precursors in explanted retina and suggests that external factors are required for maintenance of cyclin D1. The global view of gene profiles presented in this study will help define the molecular changes in retina explants over time and will provide criteria to define future changes that improve this model system

Trans-Dominant Inhibition of Prion Propagation In Vitro Is Not Mediated by an Accessory Cofactor

Previous studies identified prion protein (PrP) mutants which act as dominant negative inhibitors of prion formation through a mechanism hypothesized to require an unidentified species-specific cofactor termed protein X. To study the mechanism of dominant negative inhibition in vitro, we used recombinant PrPC molecules expressed in Chinese hamster ovary cells as substrates in serial protein misfolding cyclic amplification (sPMCA) reactions. Bioassays confirmed that the products of these reactions are infectious. Using this system, we find that: (1) trans-dominant inhibition can be dissociated from conversion activity, (2) dominant-negative inhibition of prion formation can be reconstituted in vitro using only purified substrates, even when wild type (WT) PrPC is pre-incubated with poly(A) RNA and PrPSc template, and (3) Q172R is the only hamster PrP mutant tested that fails to convert into PrPSc and that can dominantly inhibit conversion of WT PrP at sub-stoichiometric levels. These results refute the hypothesis that protein X is required to mediate dominant inhibition of prion propagation, and suggest that PrP molecules compete for binding to a nascent seeding site on newly formed PrPSc molecules, most likely through an epitope containing residue 172

Optical emission spectroscopy of electron-cyclotron-resonance-heated helium mirror plasmas

In this experiment emission spectroscopy in the 3000–5000 Å range has been utilized to determine the electron temperature (15–60 eV) and ion density (2–5 x 10 11 cm −3 ) of helium plasmas produced by the Michigan mirror machine (1) (MIMI). The plasma is generated and heated by whistler-mode electron-cyclotron resonance (ECR) waves at 7.43 GHz with 400–900 W power in 80-ms-long pulses. Gas fueling is provided at the midplane region by a leak valve with a range in pressure of 3 x 10 to 2 x 10 4 Torr. Emission line intensities are interpreted using a model of the important collisional and radiative processes occurring in the plasma. The model examines secondary processes such as radiation trapping, excitation transfer between levels of the carne principle quantum number, and excitation front metastable states for plasmas in the parameter range of MIMI ( n c = 1−6 x 10 11 cm −3 ). Front the analysis of line intensity ratios for neutral helium, the electron temperature is measured and its dependence upon the gas pressure and microwave power is determined. These temperatures agree with those obtained by Langmuir probe measurements. Art analysis of the line intensity ratio between singly ionized helium and neutral helium yields a measurement of the ion density which is in good agreement with electron density measurements made by a microwave interferometer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45473/1/11090_2005_Article_BF01447032.pd

Tutorial: Multivariate Classification for Vibrational Spectroscopy in Biological Samples

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental