Instability of the Octarepeat Region of the Human Prion Protein Gene

Prion diseases are a family of unique fatal transmissible neurodegenerative diseases that affect humans and many animals. Sporadic Creutzfeldt-Jakob disease (sCJD) is the most common prion disease in humans, accounting for 85–90% of all human prion cases, and exhibits a high degree of diversity in phenotypes. The etiology of sCJD remains to be elucidated. The human prion protein gene has an octapeptide repeat region (octarepeats) that normally contains 5 repeats of 24–27 bp (1 nonapeptide and 4 octapeptide coding sequences). An increase of the octarepeat numbers to six or more or a decrease of the octarepeat number to three is linked to genetic prion diseases with heterogeneous phenotypes in humans. Here we report that the human octarepeat region is prone to either contraction or expansion when subjected to PCR amplification in vitro using Taq or Pwo polymerase and when replicated in wild type E. coli cells. Octarepeat insertion mutants were even less stable, and the mutation rate for the wild type octarepeats was much higher when replicated in DNA mismatch repair-deficient E.coli cells. All observed octarepeat mutants resulting from DNA replication in E.coli were contained in head-to-head plasmid dimers and DNA mfold analysis (http://mfold.rna.albany.edu/?q=mfold/DNA-Folding-Form) indicates that both DNA strands of the octarepeat region would likely form multiple stable hairpin structures, suggesting that the octarepeat sequence may form stable hairpin structures during DNA replication or repair to cause octarepeat instability. These results provide the first evidence supporting a somatic octarepeat mutation-based model for human sCJD etiology: 1) the instability of the octarepeat region leads to accumulation of somatic octarepeat mutations in brain cells during development and aging, 2) this instability is augmented by compromised DNA mismatch repair in aged cells, and 3) eventually some of the octarepeat mutation-containing brain cells start spontaneous de novo prion formation and replication to initiate sCJD

A distribution-free convolution model for background correction of oligonucleotide microarray data

IntroductionAffymetrix GeneChip® high-density oligonucleotide arrays are widely used in biological and medical research because of production reproducibility, which facilitates the comparison of results between experiment runs. In order to obtain high-level classification and cluster analysis that can be trusted, it is important to perform various pre-processing steps on the probe-level data to control for variability in sample processing and array hybridization. Many proposed preprocessing methods are parametric, in that they assume that the background noise generated by microarray data is a random sample from a statistical distribution, typically a normal distribution. The quality of the final results depends on the validity of such assumptions. ResultsWe propose a Distribution Free Convolution Model (DFCM) to circumvent observed deficiencies in meeting and validating distribution assumptions of parametric methods. Knowledge of array structure and the biological function of the probes indicate that the intensities of mismatched (MM) probes that correspond to the smallest perfect match (PM) intensities can be used to estimate the background noise. Specifically, we obtain the smallest q2 percent of the MM intensities that are associated with the lowest q1 percent PM intensities, and use these intensities to estimate background. ConclusionUsing the Affymetrix Latin Square spike-in experiments, we show that the background noise generated by microarray experiments typically is not well modeled by a single overall normal distribution. We further show that the signal is not exponentially distributed, as is also commonly assumed. Therefore, DFCM has better sensitivity and specificity, as measured by ROC curves and area under the curve (AUC) than MAS 5.0, RMA, RMA with no background correction (RMA-noBG), GCRMA, PLIER, and dChip (MBEI) for preprocessing of Affymetrix microarray data. These results hold for two spike-in data sets and one real data set that were analyzed. Comparisons with other methods on two spike-in data sets and one real data set show that our nonparametric methods are a superior alternative for background correction of Affymetrix data

A gene selection method for GeneChip array data with small sample sizes

<p>Abstract</p> <p>Background</p> <p>In microarray experiments with small sample sizes, it is a challenge to estimate p-values accurately and decide cutoff p-values for gene selection appropriately. Although permutation-based methods have proved to have greater sensitivity and specificity than the regular t-test, their p-values are highly discrete due to the limited number of permutations available in very small sample sizes. Furthermore, estimated permutation-based p-values for true nulls are highly correlated and not uniformly distributed between zero and one, making it difficult to use current false discovery rate (FDR)-controlling methods.</p> <p>Results</p> <p>We propose a model-based information sharing method (MBIS) that, after an appropriate data transformation, utilizes information shared among genes. We use a normal distribution to model the mean differences of true nulls across two experimental conditions. The parameters of the model are then estimated using all data in hand. Based on this model, p-values, which are uniformly distributed from true nulls, are calculated. Then, since FDR-controlling methods are generally not well suited to microarray data with very small sample sizes, we select genes for a given cutoff p-value and then estimate the false discovery rate.</p> <p>Conclusion</p> <p>Simulation studies and analysis using real microarray data show that the proposed method, MBIS, is more powerful and reliable than current methods. It has wide application to a variety of situations.</p

Independent component analysis of Alzheimer's DNA microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA) and independent component analysis (ICA) have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics.</p> <p>Results</p> <p>ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD) hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In comparison to the PCA and support vector machine recursive feature elimination (SVM-RFE) methods, which are widely used in microarray data analysis, ICA can identify more AD-related genes. Furthermore, we have validated and identified many genes that are associated with AD pathogenesis.</p> <p>Conclusion</p> <p>We demonstrated that ICA exploits higher-order statistics to identify gene expression profiles as linear combinations of elementary expression patterns that lead to the construction of potential AD-related pathogenic pathways. Our computing results also validated that the ICA model outperformed PCA and the SVM-RFE method. This report shows that ICA as a microarray data analysis tool can help us to elucidate the molecular taxonomy of AD and other multifactorial and polygenic complex diseases.</p

Dietary magnesium and copper affect survival time and neuroinflammation in chronic wasting disease

Chronic wasting disease (CWD), the only known wildlife prion disease, affects deer, elk and moose. The disease is an ongoing and expanding problem in both wild and captive North American cervid populations and is difficult to control in part due to the extreme environmental persistence of prions, which can transmit disease years after initial contamination. The role of exogenous factors in CWD transmission and progression is largely unexplored. In an effort to understand the influence of environmental and dietary constituents on CWD, we collected and analyzed water and soil samples from CWD-negative and positive captive cervid facilities, as well as from wild CWD-endozootic areas. Our analysis revealed that, when compared with CWD-positive sites, CWD-negative sites had a significantly higher concentration of magnesium, and a higher magnesium/copper (Mg/Cu) ratio in the water than that from CWD-positive sites. When cevidized transgenic mice were fed a custom diet devoid of Mg and Cu and drinking water with varied Mg/Cu ratios, we found that higher Mg/Cu ratio resulted in significantly longer survival times after intracerebral CWD inoculation. We also detected reduced levels of inflammatory cytokine gene expression in mice fed a modified diet with a higher Mg/Cu ratio compared to those on a standard rodent diet. These findings indicate a role for dietary Mg and Cu in CWD pathogenesis through modulating inflammation in the brain

Activation of p53-regulated pro-apoptotic signaling pathways in PrP-mediated myopathy

<p>Abstract</p> <p>Background</p> <p>We have reported that doxycycline-induced over-expression of wild type prion protein (PrP) in skeletal muscles of Tg(HQK) mice is sufficient to cause a primary myopathy with no signs of peripheral neuropathy. The preferential accumulation of the truncated PrP C1 fragment was closely correlated with these myopathic changes. In this study we use gene expression profiling to explore the temporal program of molecular changes underlying the PrP-mediated myopathy.</p> <p>Results</p> <p>We used DNA microarrays, and confirmatory real-time PCR and Western blot analysis to demonstrate deregulation of a large number of genes in the course of the progressive myopathy in the skeletal muscles of doxycycline-treated Tg(HQK) mice. These include the down-regulation of genes coding for the myofibrillar proteins and transcription factor MEF2c, and up-regulation of genes for lysosomal proteins that is concomitant with increased lysosomal activity in the skeletal muscles. Significantly, there was prominent up-regulation of p53 and p53-regulated genes involved in cell cycle arrest and promotion of apoptosis that paralleled the initiation and progression of the muscle pathology.</p> <p>Conclusion</p> <p>The data provides the first <it>in vivo </it>evidence that directly links p53 to a wild type PrP-mediated disease. It is evident that several mechanistic features contribute to the myopathy observed in PrP over-expressing mice and that p53-related apoptotic pathways appear to play a major role.</p

Dietary magnesium and copper affect survival time and neuroinflammation in chronic wasting disease

Chronic wasting disease (CWD), the only known wildlife prion disease, affects deer, elk and moose. The disease is an ongoing and expanding problem in both wild and captive North American cervid populations and is difficult to control in part due to the extreme environmental persistence of prions, which can transmit disease years after initial contamination. The role of exogenous factors in CWD transmission and progression is largely unexplored. In an effort to understand the influence of environmental and dietary constituents on CWD, we collected and analyzed water and soil samples from CWD-negative and positive captive cervid facilities, as well as from wild CWD-endozootic areas. Our analysis revealed that, when compared with CWD-positive sites, CWD-negative sites had a significantly higher concentration of magnesium, and a higher magnesium/copper (Mg/Cu) ratio in the water than that from CWD-positive sites. When cevidized transgenic mice were fed a custom diet devoid of Mg and Cu and drinking water with varied Mg/Cu ratios, we found that higher Mg/Cu ratio resulted in significantly longer survival times after intracerebral CWD inoculation. We also detected reduced levels of inflammatory cytokine gene expression in mice fed a modified diet with a higher Mg/Cu ratio compared to those on a standard rodent diet. These findings indicate a role for dietary Mg and Cu in CWD pathogenesis through modulating inflammation in the brain

Detection of two dissimilar chronic wasting disease isolates in two captive Rocky Mountain elk (\u3ci\u3eCervus canadensis\u3c/i\u3e) herds: Two distinctive chronic wasting disease isolates identified in captive elk

Chronic wasting disease (CWD) continues to spread in both wild and captive cervid herds in North America and has now been identified in wild reindeer and moose in Norway, Finland and Sweden. There is limited knowledge about the variety and characteristics of isolates or strains of CWD that exist in the landscape and their implications on wild and captive cervid herds. In this study, we evaluated brain samples from two captive elk herds that had differing prevalence, history and timelines of CWD incidence. Site 1 had a 16-year history of CWD with a consistently low prevalence between 5% and 10%. Twelve of fourteen naïve animals placed on the site remained CWD negative after 5 years of residence. Site 2 herd had a nearly 40-year known history of CWD with long-term environmental accrual of prion leading to nearly 100% of naïve animals developing clinical CWD within two to 12 years. Obex samples of several elk from each site were compared for CWD prion strain deposition, genotype in prion protein gene codon 132, and conformational stability of CWD prions. CWD prions in the obex from site 2 had a lower conformational stability than those from site 1, which was independent of prnp genotype at codon 132. These findings suggest the existence of different CWD isolates between the two sites and suggest potential differential disease attack rates for different CWD strains

Glycans are not necessary to maintain the pathobiological features of bovine spongiform encephalopathy

The role of the glycosylation status of PrPC in the conversion to its pathological counterpart and on cross-species transmission of prion strains has been widely discussed. Here, we assessed the effect on strain characteristics of bovine spongiform encephalopathy (BSE) isolates with different transmission histories upon propagation on a model expressing a non-glycosylated human PrPC. Bovine, ovine and porcine-passaged BSE, and variant Creutzfeldt-Jakob disease (vCJD) isolates were used as seeds/inocula in both in vitro and in vivo propagation assays using the non-glycosylated human PrPC-expressing mouse model (TgNN6h). After protein misfolding cyclic amplification (PMCA), all isolates maintained the biochemical characteristics of BSE. On bioassay, all PMCA-propagated BSE prions were readily transmitted to TgNN6h mice, in agreement with our previous in vitro results. TgNN6h mice reproduced the characteristic neuropathological and biochemical hallmarks of BSE, suggesting that the absence of glycans did not alter the pathobiological features of BSE prions. Moreover, back-passage of TgNN6h-adapted BSE prions to BoTg110 mice recovered the full BSE phenotype, confirming that the glycosylation of human PrPC is not essential for the preservation of the human transmission barrier for BSE prions or for the maintenance of BSE strain properties