Anna Barceló

Characterization of the calcium-mediated response to alkaline stress in saccharomyces cerevisiae

Exposure of the yeast Saccharomyces cerevisiae to alkaline stress resulted in adaptive changes that involved remodeling the gene expression. Recent evidence suggested that the calcium-activated protein phosphatase calcineurin could play a role in alkaline stress signaling. By using an aequorin luminescence reporter, we showed that alkaline stress resulted in a sharp and transient rise in cytoplasmic calcium. This increase was largely abolished by addition of EGTA to the medium or in cells lacking Mid1 or Cch1, components of the high affinity cell membrane calcium channel. Under these circumstances, the alkaline response of different calcineurin-sensitive transcriptional promoters was also blocked. Therefore, exposure to alkali resulted in entry of calcium from the external medium, and this triggered a calcineurin-mediated response. The involvement of calcineurin and Crz1/Tcn1, the transcription factor activated by the phosphatase, in the transcriptional response triggered by alkalinization has been globally assessed by DNA microarray analysis in a time course experiment using calcineurin-deficient (cnb1) and crz1 mutants. We found that exposure to pH 8.0 increased at least 2-fold the mRNA levels of 266 genes. In many cases (60%) the response was rather early (peak after 10 min). The transcriptional response of 27 induced genes (10%) was reduced or fully abolished in cnb1 cells. In general, the response of crz1 mutants was similar to that of calcineurin-deficient cells. By analysis of a systematic deletion library, we found 48 genes whose mutation resulted in increased sensitivity to the calcineurin inhibitor FK506. Twenty of these mutations (42%) also provoked alkaline pH sensitivity. In conclusion, our results demonstrated that calcium signaling and calcineurin activation represented a significant component of the yeast response to environmental alkalinization.

Functional Characterization of the Yeast Ppz1 Phosphatase Inhibitory Subunit Hal3 A MUTAGENESIS STUDY

Saccharomyces cerevisiae Hal3 is a conserved protein that binds the carboxyl-terminal catalytic domain of the PP1c (protein phosphatase 1)-related phosphatase Ppz1 and potently inhibits its activity, thus modulating all of the characterized functions so far of the phosphatase. It is unknown how Hal3 binds to Ppz1 and inhibits its activity. Although it contains a putative protein phosphatase 1c binding-like sequence (263KLHVLF268), mutagenesis analysis suggests that this motif is not required for Ppz1 binding and inhibition. The mutation of the conserved His378 (possibly involved in dehydrogenase catalytic activity) did not impair Hal3 functions or Ppz1 binding. Random mutagenesis of the 228 residue-conserved central region of Hal3 followed by a loss-of-function screen allowed the identification of nine residues important for Ppz1-related Hal3 functions. Seven of these residues cluster in a relatively small region spanning from amino acid 446 to 480. Several mutations affected Ppz1 binding and inhibition in vitro, whereas changes in Glu460 and Val462 did not alter binding but resulted in Hal3 versions unable to inhibit the phosphatase. Therefore, there are independent Hal3 structural elements required for Ppz1 binding and inhibition. S. cerevisiae encodes a protein (Vhs3) structurally related to Hal3. Recent evidence suggests that both mutations are synthetically lethal. Surprisingly, versions of Hal3 carrying mutations that strongly affected Ppz1 binding or inhibitory capacity were able to complement lethality. In contrast, the mutation of His378 did not. This finding suggests that Hal3 may have both Ppz1-dependent and independent functions involving different structural elements.

Mutagenesis analysis of the yeast Nha1 Na+/H+ antiporter carboxy-terminal tail reveals residues required for function in cell cycle.

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.

Functional analysis of the Neurospora crassa PZL-1 protein phosphatase by expression in budding and fission yeast

The gene pzl‐1 from the filamentous fungus Neurospora crassa encodes a putative Ser/Thr protein phosphatase that is reminiscent of the Ppz1/Ppz2 and Pzh1 phosphatases from Saccharomyces cerevisiae and Schizosaccharomyces pombe, respectively. The entire PZL‐1 protein, as well as its carboxyl‐terminal domain, have been expressed in Escherichia coli as active protein phosphatases. To characterize its cellular role, PZL‐1 was also expressed in Sz. pombe and in S. cerevisiae. Expression of PZL‐1 in S. cerevisiae from the PPZ1 promoter was able to rescue the altered sensitivity to caffeine and lithium ions of a ppz1 strain. Furthermore, high copy number expression of PZL‐1 alleviated the lytic phenotype of a S. cerevisiae slt2/mpk1 mitogen‐activated protein (MAP) kinase mutant, similarly to that described for PPZ1, and mimicked the effects of high levels of Ppz1 on cell growth. Expression of PZL‐1 in fission yeast from a weak version of the nmt1 promoter fully rescued the growth defect of a pzh1Δ strain in high potassium, but only partially complemented the sodium‐hypertolerant phenotype. Strong overexpression of the N. crassa phosphatase in Sz. pombe affected cell growth and morphology. Therefore, PZL‐1 appears to fulfil every known function carried out by its S. cerevisiae counterpart, despite the marked divergence in sequence within their NH2‐terminal moieties. Copyright

Automated brain tumor biopsy prediction using single-labeling cDNA microarrays-based gene expression profiling.

Aims Gene signatures obtained from microarray experiments may be of use to improve the prediction of brain tumor diagnosis. Nevertheless, automated and objective prediction with accuracy comparable to or better than the gold standard should be convincingly demonstrated for possible clinician uptake of the new methodology. Herewith, we demonstrate that primary brain tumor types can be discriminated using microarray data in an automated and objective way. Methods Postsurgical biopsies from 35 patients [17 glioblastoma multiforme (Gbm) and 18 meningothelial meningioma (Mm)] were stored in liquid nitrogen, total RNA was extracted, and cDNA was labeled with Cy3 fluorochrome and hybridized onto a cDNA-based microarray containing 11,500 cDNA clones representing 9300 loci. Scanned data were preprocessed, normalized, and used for predictor development. The predictive functions were fitted to a subset of samples and their performance evaluated with an independent subset. Expression results were validated by means of real time-polymerase chain reaction. Results Some gene expression-based predictors achieved 100% accuracy both in training resampling validation and independent testing. One of them, composed of GFAP, PTPRZ1, GPM6B and PRELP, produced a 100% prediction accuracy for both training and independent test datasets. Furthermore, the gene signatures obtained, increased cell detoxification, motility and intracellular transport in Gbm, and increased cell adhesion and cytochrome-family genes in Mm, agree well with the expected biologic and pathologic characteristics of the studied tumors. Conclusions The ability of gene signatures to automate prediction of brain tumors through a fully objective approach has been demonstrated. A comparison of gene expression profiles between Gbm and Mm may provide additional clues about patterns associated with each tumor type.

Strategies for annotation and curation of translational databases: the eTUMOUR project

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.

Central nervous system gene expression changes in a transgenic mouse model for bovine spongiform encephalopathy.

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.

Development of a Predictor for Human Brain Tumors Based on Gene Expression Values Obtained from Two Types of Microarray Technologies

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.

Development of robust discriminant equations for assessing subtypes of glioblastoma biopsies.

Background:In the preceding decade, various studies on glioblastoma (Gb) demonstrated that signatures obtained from gene expression microarrays correlate better with survival than with histopathological classification. However, there is not a universal consensus formula to predict patient survival.Methods:We developed a gene signature using the expression profile of 47 Gbs through an unsupervised procedure and two groups were obtained. Subsequent to a training procedure through leave-one-out cross-validation, we fitted a discriminant (linear discriminant analysis (LDA)) equation using the four most discriminant probesets. This was repeated for two other published signatures and the performance of LDA equations was evaluated on an independent test set, which contained status of IDH1 mutation, EGFR amplification, MGMT methylation and gene VEGF expression, among other clinical and molecular information.Results:The unsupervised local signature was composed of 69 probesets and clearly defined two Gb groups, which would agree with primary and secondary Gbs. This hypothesis was confirmed by predicting cases from the independent data set using the equations developed by us. The high survival group predicted by equations based on our local and one of the published signatures contained a significantly higher percentage of cases displaying IDH1 mutation and non-amplification of EGFR. In contrast, only the equation based on the published signature showed in the poor survival group a significant high percentage of cases displaying a hypothesised methylation of MGMT gene promoter and overexpression of gene VEGF.Conclusion:We have produced a robust equation to confidently discriminate Gb subtypes based in the normalised expression level of only four genes.

Genomics and metabolomics research for brain tumour diagnosis based on machine learning

The incorporation of new biomedical technologies in the diagnosis and prognosis of cancer is changing medicine to an evidence-based diagnosis. We summarize some studies related to brain tumour research in Europe, based on the metabolic information provided by in vivo Magnetic Resonance Spectroscopy (MRS) and transcriptomic profiling observed by DNA microarrays. The first result presents the improvement in brain tumour diagnosis by combining Long TE and Short TE single voxel MR Spectra. Afterwards, a mixture model for binned and truncated data to characterize and classify MRS is reviewed. The classification of Glioblastomas Multiforme and Meningothelial Meningiomas using single-labeling cDNA-based microarrays was studied as proof of principle in the incorporation of genomic information to clinical diagnosis. Finally, we present a Decision Support System for in-vivo classification of brain tumours were the best inferred classifiers are deployed for their clinical use.