Project description:Metabolic abnormalities underlying diabetes are primarily the result of the lack of adequate insulin action and the associated changes in protein phosphorylation and gene expression. Affymetrix oligonucleotide microarrays were used to study the changes in the transcriptional program of mouse skeletal muscle in insulin-deficient diabetes. Mice which were made diabetic by streptozotocin treatment were compared to controls. Also, the reversibility of these changes was ascertained by treating a subset of the diabetic mice with insulin.
Project description:The myeloma cell line RPMI 8226/S and its doxorubicin resistant subline 8226/Dox40 were used as models to explore the potential importance of the STAT1 signaling pathway in drug and radiation resistance. The 40-fold doxorubicin resistant subline 8226/Dox40 was found to be crossresistant to single doses of 4 and 8 Gy of radiation. A genome-wide mRNA expression study comparing the 8226/Dox40 cell line to its parental line was performed to identify the underlying molecular mechanisms. Seventeen of the top 50 overexpressed genes have previously been implicated in the STAT1 signaling pathway. STAT1 was over expressed both at the mRNA and protein level. Moreover, analyses of nuclear extracts showed higher abundance of phosphorylated STAT1 (Tyr 701) in the resistant subline. Preexposure of the crossresistant cells to the STAT1 inhibiting drug fludarabine reduced expression of overexpressed genes and enhanced the effects of both doxorubicin and radiation. These results show that resistance to doxorubicin and radiation is associated with increased STAT1 signaling and can be modulated by fludarabine. The data support further development of therapies combining fludarabine and radiation.
Project description:We investigated genome-wide changes in mRNA translation in Arabidopsis thaliana suspension cell cultures exposed to brief perids of two types of stress: elevated temperature (37 degree_C) and high salinity (200 mM NaCl). To this end, we subjected polysomal RNA and non-polysomal RNA from sucrose gradient fractionated cell lysates to the co-hybridization on Agilent Arabidopsis 3 Oligo Microarrays. The ratio of signal intensities (polysomal RNA: non-polysomal RNA) was used as an indicator of the translation state for each transcript. To inspect coordination of changes in translational profiles with transcriptional profiles, we also isolated total RNAs from the same cells used for translational profiling experiments and investigated changes in accumulated transcript levels in response to each stress using the microarray. Two biological replicates were analyzed.
Project description:Combining or pooling individual samples when carrying out transcript profiling using microarrays is a fairly common means to reduce both the cost and complexity of data analysis. However, pooling does not allow for statistical comparison of changes between samples and can result in a loss of information. Because a rigorous comparison of the identified expression changes from the two approaches has not been reported, we compared the results for hepatic transcript profiles from pooled vs. individual samples. Hepatic transcript profiles from a single-dose time-course rat study in response to the prototypical toxicants Clofibrate [CAS:637-07-0;CHEBI:3750], Diethylhexyl phthalate DEHP [CAS:117-81-7;CHEBI:17243], and valproic acid VPA [CAS:1069-66-5;CHEBI:9925],were evaluated. Approximately 50% more transcript expression changes were observed in the individual (statistical) analysis compared with the pooled analysis. While the majority of these changes were less than twofold in magnitude (~80%), a substantial number were greater than twofold (~20%). Transcript changes unique to the individual analysis were confirmed by quantitative RT-PCR, while all the changes unique to the pooled analysis did not confirm. The individual analysis identified more hits per biological pathway than the pooled approach. Many of the transcripts identified by the individual analysis were novel findings and may contribute to a better understanding of molecular mechanisms of these compounds. Furthermore, having individual animal data provided the opportunity to correlate changes in transcript expression to phenotypes (i.e., histology) observed in toxicology studies. The two approaches were similar when clustering methods were used despite the large difference in the absolute number of transcripts changed. In summary, pooling reduced resource requirements substantially, but the individual approach enabled statistical analysis that identified more gene expression changes to evaluate mechanisms of toxicity. An individual animal approach becomes more valuable when the overall expression response is subtle and/or when associating expression data to variable phenotypic responses.
Project description:BACKGROUND: The use of gene expression profiling in both clinical and laboratory settings would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies could yield useful information on baseline fluctuations in gene expression, although control animal data has not been available on a scale and in a form best served for data-mining. RESULTS: A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. CONCLUSIONS: The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selective, or altered by fasting were also identified and functionally categorized. Better characterization of gene expression variability in control animals will aid in the design of toxicogenomics studies and in the interpretation of their results. [based on information contained in Final_HESI_Decoder_483_05_015_07.txt provided by CEBS database]
Project description:Viral infections and local production of IFNgamma might contribute to beta-cell dysfunction/death in Type 1 diabetes. Double stranded RNA accumulates in the cytosol of viral-infected cells, and exposure of purified rat beta cells to dsRNA (polyinosinic-polycytidylic acid, PIC) in combination with IFNgamma results in beta-cell dysfunction and apoptosis. To elucidate the molecular mechanisms involved in PIC + IFNgamma-effects, we determined the global profile of genes modified by these agents in primary rat beta cells. FACS-purified rat beta cells were cultured for 6 or 24 h in control condition or with IFNgamma, PIC or a combination of both agents. The gene expression profile was analyzed in duplicate with the Affymetrix RG U34A microarray.