E-GEOD-1659 - Transcription profiling of mouse time series of diabetes and exercise training induced expression changes in skeletal muscle
Submitted on 11 August 2004, released on 24 October 2007, last updated on 1 May 2014
Experiment protocol: Experiment was performed on 10 to 15 weeks old male NMRI mice (Harlan, Holland) housed in standard conditions (temperature 22°C, humidity 60 ± 10 %, artificial light from 8.00 am to 8.00 pm, normally 5 animals per cage). Animals had free access to tap water and food pellets (R36, Labfor, Stockholm, Sweden). Animals were randomly divided into healthy and diabetic groups. The diabetic group received a single peritoneal injection of streptozotocin (STZ, Sigma-Aldrich, France, 180 mg/kg) dissolved in sodium citrate buffer solution (0.1 mol/l, pH 4.5) to induce experimental diabetes similar to type 1. The other group received injection of an equal volume of buffer. Diabetes was confirmed 72 hours after the injection by urine glucose testing (Glukotest(r), Roche, Germany), and mice were characterized diabetic when urine glucose values were greater than 200 mg/dl. Diabetic and healthy animals were randomly assigned into 12 groups (n = 5 per group), which were sedentary or trained for one, three or five weeks. Training groups performed 1 hour per day of treadmill running at 21 m/min and 2.5° incline. After one day of familiarization on a rodent treadmill, the mice ran as described above 5 days per week. Mice were sacrificed 24 hours after the last training bout (respective sedentary controls at the same time) by cervical dislocation followed by decapitation. Calf muscles were removed, dissected free of fat and connective tissue, weighed, snap frozen in liquid nitrogen and stored at -80°C for further analysis. Total RNA extraction and sample preparation: Total RNA was extracted from the left calf muscle complex (soleus + gastrocnemius + plantaris) with Trizol Reagent (Invitrogen, Carlsbad, CA) and further purified with RNeasy columns (Qiagen, Valencia, CA) according to the manufacturers' protocols. Concentration and purity of RNA was determined by measuring absorbances at wavelengths 260 and 280 nm. Integrity of the RNA was checked with agarose gel electrophoresis. RNA samples were pooled within each group for microarray analyses. Concentration, purity and integrity of pooled RNA samples were checked as described above. Micro array analysis: Pooled RNA samples were analyzed with Affymetrix Gene Chip MG U74Av2 (Affymetrix, Inc., Santa Clara, CA) representing 6000 known genes and 6000 ESTs. Microarray analyses were performed according to the instructions of Affymetrix. Briefly, 5 µg of total pooled RNA was reverse transcribed using T7-(dT)24-primers and SuperScript II RT enzyme (Invitrogen). Single stranded cDNA was turned to double stranded cDNA using T4 DNA polymerase (Invitrogen). Produced cDNA was then purified and transcribed in vitro to biotin labeled cRNA using Enzo Bioarray High Yield RNA Transcript Labeling Kit (Enzo Diagnostics, Farmingdale, NY). RNA was purified and its quality was checked. Purity and quantity of RNA was measured with Nanodrop ND-1000 Spectrophotometer (Nanodrop Technologies, Montchanin, DE) and integrity was tested with agarose gel electrophoresis. Sample was then fragmented and hybridized to Affymetrix test chip to check the function of the hybridization cocktail and to ensure adequate representation of both 5' and 3' ends of the RNA. After testing, samples (15 µg) were hybridized to expression chips. After hybridization, chips were washed and stained in Affymetrix Fluidics Station 400. Arrays were stained first with R-Phycoerythrin Streptavidin (Molecular Probes, Eugene, OR), then with biotinylated anti-streptavidin antibody (Vector Laboratories, Burlingame, CA) and again with R-Phycoerythrin Streptavidin for signal enhancement. The chip was scanned with GeneArray Scanner G2500A (Agilent, Palo Alto, CA); Scaling and normalization of data: The array images were analyzed with Microarray Suite 5.0 (Affymetrix) software. All chips were scaled (global scaling) to target intensity of 50 to minimize differences between chips caused by physical differences in chips, hybridization efficiencies and manual laboratory work. The data was subjected to robust normalization that reduces the errors, which are caused by binding capacity and linearity differences between probe sets.
transcription profiling by array, co-expression, disease state, time series
Effects of streptozotocin-induced diabetes and physical training on gene expression of extracellular matrix proteins in mouse skeletal muscle. T Maarit Lehti, Mika Silvennoinen, Riikka Kivelä, Heikki Kainulainen, Jyrki Komulainen. Am J Physiol Endocrinol Metab 290(5):E900-7 (2006)