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Biomedical subjects

Rodney Ouellette

Publications and source records attributed to Rodney Ouellette.

3 recordsLinked to original sources

RiboSubstrates: a web application addressing the cleavage specificities of ribozymes in designated genomes.

BACKGROUND: RNA-dependent gene silencing is becoming a routine tool used in laboratories worldwide. One of the important remaining hurdles in the selection of the target sequence, if not the most important one, is the designing of tools that have minimal off-target effects (i.e. cleaves only the desired sequence). Increasingly, in the current dawn of the post-genomic era, there is a heavy reliance on tools that are suitable for high-throughput functional genomics, consequently more and more bioinformatic software is becoming available. However, to date none have been designed to satisfy the ever-increasing need for the accurate selection of targets for a specific silencing reagent. RESULTS: In order to overcome this hurdle we have developed RiboSubstrates http://www.riboclub.org/ribosubstrates. This integrated bioinformatic software permits the searching of a cDNA database for all potential substrates for a given ribozyme. This includes the mRNAs that perfectly match the specific requirements of a given ribozyme, as well those including Wobble base pairs and mismatches. The results generated allow rapid selection of sequences suitable as targets for RNA degradation. The current web-based RiboSubstrates version permits the identification of potential gene targets for both SOFA-HDV ribozymes and for hammerhead ribozymes. Moreover, a minimal template for the search of siRNAs is also available. This flexible and reliable tool is easily adaptable for use with any RNA tool (i.e. other ribozymes, deoxyribozymes and antisense), and may use the information present in any cDNA bank. CONCLUSION: RiboSubstrates should become an essential step for all, even including "non-RNA biologists", who endeavor to develop a gene-inactivation system.

Animals↗

Expression of melatoninergic receptors in human placental choriocarcinoma cell lines.

BACKGROUND: Melatonin crosses the placenta and enters the fetal circulation. Moreover, experimental data suggest a possible influence of melatonin on placental function and fetal development in humans. To date, the expression and role of melatonin receptors in human placenta choriocarcinoma cell lines and in human term placental tissues remain to be elucidated. METHODS AND RESULTS: Results from RT-PCR, western blotting and confocal microscopy demonstrated that the MT1, MT2 and RORalpha1 melatonin receptors are expressed in the human term placental tissues and in choriocarcinoma cell lines JEG-3 and BeWo. Furthermore, enzyme-linked immunosorbent assay showed that 6-chloromelatonin (a melatonin agonist) inhibits, in a dose-dependent manner, forskolin-stimulated hCG-beta secretion in JEG-3 (P < 0.001) and BeWo (P < 0.05) cells but had no effect on basal human chorionic gonadotrophin (hCG-beta) levels. This effect of 6-chloromelatonin on forskolin-stimulated HCG-beta secretion was abolished by pertussis toxin (PTX), suggesting that melatonin regulates hCG-beta production by an action involving an inhibitory Gi/o protein. In PTX-treated BeWo cells, 6-chloromelatonin stimulated basal hCG-beta secretion (P < 0.001). CONCLUSION: These results demonstrate, for the first time, the expression of melatonin receptors in human term placental tissues and in choriocarcinoma cells and suggest a possible paracrine/autocrine function for melatonin in human placenta.

Cell Line, Tumor↗

Fuzzy J-Means and VNS methods for clustering genes from microarray data.

MOTIVATION: In the interpretation of gene expression data from a group of microarray experiments that include samples from either different patients or conditions, special consideration must be given to the pleiotropic and epistatic roles of genes, as observed in the variation of gene coexpression patterns. Crisp clustering methods assign each gene to one cluster, thereby omitting information about the multiple roles of genes. RESULTS: Here, we present the application of a local search heuristic, Fuzzy J-Means, embedded into the variable neighborhood search metaheuristic for the clustering of microarray gene expression data. We show that for all the datasets studied this algorithm outperforms the standard Fuzzy C-Means heuristic. Different methods for the utilization of cluster membership information in determining gene coregulation are presented. The clustering and data analyses were performed on simulated datasets as well as experimental cDNA microarray data for breast cancer and human blood from the Stanford Microarray Database. AVAILABILITY: The source code of the clustering software (C programming language) is freely available from Nabil.Belacel@nrc-cnrc.gc.ca

Algorithms↗