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Abstract Gene expression analysis has proven to be a very useful tool to gain knowledge of the factors involved in the pathogenesis of diseases, particularly in the initial or preclinical stages. With the aim of finding new data on the events occurring in the Central Nervous System in animals affected with Bovine Spongiform Encephalopathy, a comprehensive genome wide gene expression study was conducted at different time points of the disease on mice genetically modified to model the bovine species brain in terms of cellular prion protein. An accurate analysis of the information generated by microarray technique was the key point to assess the biological relevance of the data obtained in terms of Transmissible Spongiform Encephalopathy pathogenesis. Validation of the microarray technique was achieved by RT-PCR confirming the RNA change and immunohistochemistry techniques that verified that expression changes were translated into variable levels of protein for selected genes. Our study reveals changes in the expression of genes, some of them not previously associated with prion diseases, at early stages of the disease previous to the detection of the pathological prion protein, that might have a role in neuronal degeneration and several transcriptional changes showing an important imbalance in the Central Nervous System homeostasis in advanced stages of the disease. Genes whose expression is altered at early stages of the disease should be considered as possible therapeutic targets and potential disease markers in preclinical diagnostic tool development. Genes non-previously related to prion diseases should be taken into consideration for further investigations.

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Lack of the yeast Ptc1 Ser/Thr protein phosphatase results in numerous phenotypic defects. A parallel search for high-copy number suppressors of three of these phenotypes (sensitivity to Calcofluor White, rapamycin and alkaline pH), allowed the isolation of 25 suppressor genes, which could be assigned to three main functional categories: maintenance of cell wall integrity (CWI), vacuolar function and protein sorting, and cell cycle regulation. The characterization of these genetic interactions strengthens the relevant role of Ptc1 in downregulating the Slt2-mediated CWI pathway. We show that under stress conditions activating the CWI pathway the ptc1 mutant displays hyperphosphorylated Cdc28 kinase and that these cells accumulate with duplicated DNA content, indicative of a G2-M arrest. Clb2-associated Cdc28 activity was also reduced in ptc1 cells. These alterations are attenuated by mutation of the MKK1 gene, encoding a MAP kinase kinase upstream Slt2. Therefore, our data show that Ptc1 is required for proper G2-M cell cycle transition after activation of the CWI pathway. [ABSTRACT FROM AUTHOR]

The yeast Nha1 Na+,K+/H+ antiporter may play an important role in regulation of cell cycle, as high-copy expression of the NHA1 gene is able to rescue the blockage at the G1/S transition of cells lacking Sit4 protein phosphatase and Hal3 activities. Interestingly, this function was independent of the role of the antiporter in improving tolerance to sodium cations, it required the integrity of a relatively large region (from residues 800 to 948) of its carboxy-terminal moiety, and was not performed by the fission yeast homolog antiporter Sod2, which lacks a carboxy-terminal tail. Here we show that a hybrid protein composed of the Sod2 antiporter fused to the carboxy-terminal half of Nha1 strongly increased sodium tolerance, but did not allow growth at high potassium nor did rescue growth of the sit4 hal3 conditional mutant strain. Deletion of Nha1 residues from 800 to 849, 900 to 925 or 926 to 954 abolished the function of Nha1 in cell cycle without affecting sodium tolerance. A screening for loss-of-function mutations at the 775–980 carboxy-terminal tail of Nha1 has revealed a number of residues required for function in cell cycle, most of them clustering in two regions, from residues 869 to 876 (cluster A) and 918 to 927 (cluster B). The later is rather conserved in other related antiporters, while the former is not. [Copyright &y& Elsevier]

The eTUMOUR (eT) multi-centre project gathered in vivo and ex vivo magnetic resonance (MR) data, as well as transcriptomic and clinical information from brain tumour patients, with the purpose of improving the diagnostic and prognostic evaluation of future patients. In order to carry this out, among other work, a database—the eTDB—was developed. In addition to complex permission rules and software and management quality control (QC), it was necessary to develop anonymization, processing and data visualization tools for the data uploaded. It was also necessary to develop sophisticated curation strategies that involved on one hand, dedicated fields for QC-generated meta-data and specialized queries and global permissions for senior curators and on the other, to establish a set of metrics to quantify its contents. The indispensable dataset (ID), completeness and pairedness indices were set. The database contains 1317 cases created as a result of the eT project and 304 from a previous project, INTERPRET. The number of cases fulfilling the ID was 656. Completeness and pairedness were heterogeneous, depending on the data type involved. [ABSTRACT FROM AUTHOR]

An abstract of the article "Trimeric Autotransporters of Haemophilus parasuis: Generation of an Extensive Passenger Domain Repertoire Specific for Pathogenic Strains," by Sonia Pina, Alex Olvera, Anna Barceló, and Albert Bensaid is presented.

Glioblastoma (Gb) is one of the most deadly tumors. Its molecular subtypes are yet to be fully characterized while the attendant efforts for personalized medicine need to be intensified in relation to glioblastoma diagnosis, treatment, and prognosis. Several molecular signatures based on gene expression microarrays were reported, but the use of microarrays for routine clinical practice is challenged by attendant economic costs. Several authors have proposed discriminant equations based on RT-PCR. Still, the discriminant threshold is often incompletely described, which makes proper validation difficult. In a previous work, we have reported two Gb subtypes based on the expression levels of four genes: CHI3L1, LDHA, LGALS1, and IGFBP3. One Gb subtype presented with low expression of the four genes mentioned, and of MGMT in a large portion of the patients (with anticipated high methylation of its promoter), and mutated IDH1. Here, we evaluate the robustness of the equations fitted with these genes using RT-PCR values in a set of 64 cases and importantly, define an unequivocal discriminant threshold with a view to prognostic implications. We developed two approaches to generate the discriminant equations: 1) using the expression level of the four genes mentioned above, and 2) using those genes displaying the highest correlation with survival among the aforementioned four ones, plus MGMT, as an attempt to further reduce the number of genes. The ease of equations' applicability, reduction in cost for raw data, and robustness in terms of resampling-based classification accuracy warrant further evaluation of these equations to discern Gb tumor biopsy heterogeneity at molecular level, diagnose potential malignancy, and prognosis of individual patients with glioblastomas.

The eTUMOUR (eT) multi-centre project gathered in vivo and ex vivo magnetic resonance (MR) data, as well as transcriptomic and clinical information from brain tumour patients, with the purpose of improving the diagnostic and prognostic evaluation of future patients. In order to carry this out, among other work, a database--the eTDB--was developed. In addition to complex permission rules and software and management quality control (QC), it was necessary to develop anonymization, processing and data visualization tools for the data uploaded. It was also necessary to develop sophisticated curation strategies that involved on one hand, dedicated fields for QC-generated meta-data and specialized queries and global permissions for senior curators and on the other, to establish a set of metrics to quantify its contents. The indispensable dataset (ID), completeness and pairedness indices were set. The database contains 1317 cases created as a result of the eT project and 304 from a previous project, INTERPRET. The number of cases fulfilling the ID was 656. Completeness and pairedness were heterogeneous, depending on the data type involved.

Development of molecular diagnostics that can reliably differentiate amongst different subtypes of brain tumors is an important unmet clinical need in postgenomics medicine and clinical oncology. A simple linear formula derived from gene expression values of four genes (GFAP, PTPRZ1, GPM6B, and PRELP) measured from cDNA microarrays (n = 35) have distinguished glioblastoma and meningioma cases in a previous study. We herein extend this work further and report that the above predictor formula showed its robustness when applied to Affymetrix microarray data acquired prospectively in our laboratory (n = 80) as well as publicly available data (n = 98). Importantly, GFAP and GPM6B were both retained as being significant in the predictive model upon using the Affymetrix data obtained in our laboratory, whereas the other two predictor genes were SFRP2 and SLC6A2. These results collectively indicate the importance of the expression values of GFAP and GPM6B genes sampled from the two types of microarray technologies tested. The high prediction accuracy obtained in these instances demonstrates the robustness of the predictors across microarray platforms used. This result would require further validation with a larger population of meningioma and glioblastoma cases. At any rate, this study paves the way for further application of gene signatures to more stringent biopsy discrimination challenges.

The yeast Saccharomyces cerevisiae has been widely used for the implementation of DNA chip technologies. For this reason and due to the extensive use of this organism for basic and applied studies, yeast DNA chips are being used by many laboratories for expression or genomic analyses. While membrane arrays (macroarrays) offer several advantages, for many laboratories they are not affordable. Here we report that a cluster of four Spanish molecular-biology yeast laboratories, with relatively small budgets, have developed a complete set of probes for the genome of S. cerevisiae. These have been used to produce a new type of macroarray on a nylon surface. The macroarrays have been evaluated and protocols for their use have been optimized.