DOI: 10.20348/storedb/1171/1246
title: Activation of PPAR alpha by fenofibrate attenuates the effect of local heart high dose irradiation on the mouse cardiac proteome
title: proteomics on fenofibrate treated mice

description: Radiation-induced cardiovascular disease is associated with the metabolic remodelling in the heart mainly due to disruption of the PPAR alpha signalling pathway and inhibition of lipid metabolic enzymes. The goal of the present study was to investigate the potential protective effect of fenofibrate-activation of PPARon radiation-induced cardiac toxicity. To this end, we compared, for the first time, the cardiac proteome of fenofibrate- and placebo-treated mice after local heart irradiation using label-free proteomics. The observations were further validated using immunoblotting, enzyme activity assays, and ELISA. The analysis showed that fenofibrate restores the affected pathways involved in lipid metabolism, mitochondrial function, oxidative stress damage, tissue remodelling and systematic inflammatory response. The results collectively presented here indicate that PPARactivation by fenofibrate attenuates the cardiac proteome alterations induced by irradiation. These findings suggest a potential benefit of PPAR alpha agonists administration in the prevention of cardiovascular diseases following radiotherapy.
description: The heart samples obtained from at least 5 mice per group were grounded to a fine powder with a cold (-20°C) mortar and pestle before being suspended in lysis buffer (SERVA)[11]. Protein concentration was determined by the Bradford assay following the manufacturers instructions (ThermoFisher, Wilmington, Massachusetts, USA). Protein lysates (10 µg) were digested using a modified filter-aided sample preparation (FASP) protocol [27] After reduction and alkylation using DTT and IAA, the proteins were centrifuged on a 30 kDa cutoff filter device (Sartorius), washed thrice with UA buffer (8 M urea in 0.1 M Tris/HCl pH 8.5) and twice with 50 mM ammoniumbicarbonate. The proteins were digested for 2 hours at room temperature using 0.5 µg Lys-C (Wako Chemicals, Neuss, Germany) and for 16 hours at 37°C using 1 µg trypsin (Promega, Mannheim, Germany). After centrifugation (10 min at 14 000 g) the eluted peptides were acidified with 0.5% TFA and stored at -20°C.LC-MS/MS analysis was performed on a Q-Exactive HF mass spectrometer (Thermo Scientific) online coupled to an Ultimate 3000 nano-RSLC (Dionex). Tryptic peptides were automatically loaded on a C18 trap column (300 µm inner diameter (ID) × 5 mm, Acclaim PepMap100 C18, 5 µm, 100 Å, LC Packings) at 30µl/min flow rate prior to C18 reversed phase chromatography on the analytical column (nanoEase MZ HSS T3 Column, 100Å, 1.8 µm, 75 µm x 250 mm, Waters) at 250nl/min flow rate in a 95 minutes non-linear acetonitrile gradient from 3 to 40% in 0.1% formic acid. Profile precursor spectra from 300 to 1500 m/z were recorded at 60000 resolution with an automatic gain control (AGC) target of 3e6 and a maximum injection time of 50 ms. TOP10 fragment spectra of charges 2 to 7 were recorded at 15000 resolution with an AGC target of 1e5, a maximum injection time of 50 ms, an isolation window of 1.6 m/z, a normalized collision energy of 27 and a dynamic exclusion of 30 seconds.Generated raw files were analyzed using Progenesis QI for proteomics (version 4.0, Nonlinear Dynamics, part of Waters) for label-free quantification as described previously [28, 29]. Features of charges 2-7 were used and all MSMS spectra were exported as mgf file. Peptide search was performed using Mascot search engine (version 2.6.2) against the Swissprot mouse protein database (16872 sequences, 9512882 residues). Search settings were: 10 ppm precursor tolerance, 0.02 Da fragment tolerance, one missed cleavage allowed. Carbamidomethyl on cysteine was set as fixed modification, deamidation of glutamine and asparagine allowed as variable modification, as well as oxidation of methionine. Applying the percolator algorithm resulted in a peptide false discovery rate (FDR) of 0.36%. Search results were reimported in the Progenesis QI software. Proteins were quantified by summing up the abundances of all unique peptides per protein. Resulting normalized protein abundances were used for calculation of fold-changes and statistical values were exported from the Progenesis QI software. For final quantifications, proteins identified with more than one unique peptide having ratios greater than 1.30-fold or less than 0.77-fold (p-value 0.05) were defined as being significantly differentially expressed.