E-GEOD-48951 - Psychotropic drug-induced gene expression alterations in mouse striatum I
Released on 18 July 2013, last updated on 3 June 2014
To identify the molecular mechanisms that may initiate therapeutic effects, whole-genome expression profiling (Illumina Mouse WG-6 microarrays) of drug-induced alterations in the mouse brain was undertaken, with a focus on the time-course (1, 2, 4 and 8h) of gene expression changes produced by eighteen major psychotropic drugs: antidepressants, antipsychotics, anxiolytics, psychostimulants and opioids. The resulting database is freely accessible at www.genes2mind.org. Bioinformatics approaches led to the identification of three main drug-responsive genomic networks and indicated neurobiological pathways that mediate the alterations in transcription. Each tested psychotropic drug was characterized by a unique gene network expression profile related to its neuropharmacological properties. Functional links that connect expression of the networks to the development of neuronal adaptations (MAPK signaling pathway), control of brain metabolism (adipocytokine pathway), and organization of cell projections (mTOR pathway) were found. The additional data-sets are available at GEOX1 and GEOX2. The microarray experiment was performed to analyze time-course of drug-induced transcriptional response in C57BL/6J mouse striatum. Three antidepressants (imipramine 10 mg/kg, fluoxetine 20 mg/kg and tianeptine 20 mg/kg, i.p.) were selected for the comparison. Drug doses were previously reported as effective in mice and further tested in our laboratory. To analyze dynamics of early, intermediate and relatively late changes of mRNA abundance the experiment was performed in four time points (1, 2, 4 and 8h after drug administration). To exclude influence of drug injection and circadian rhythm on gene expression profile, control groups of saline treated and naïve animals were prepared for each time point. Design of the experiment assumed pooling of two animals per each array and using of three independent arrays per group. To provide appropriate balance in the whole dataset groups were equally divided between the array hybridization batches.
transcription profiling by array
Marcin Piechota <email@example.com>, M Korostynski, M Piechota