DOI: 10.5061/dryad.x95x69pm1
title: Lipidomic data of iRECs treated with palmitic acid and oleic acid

description: In diabetic patients, dyslipidemia frequently contributes to organ damage
 such as diabetic kidney disease (DKD). DKD is associated with excessive
 renal deposition of triacylglycerol (TAG) in lipid droplets (LD). In order
 to identify the changes in the lipidome of proximal tubules exposed to
 high levels of fatty acids and the role that LDs formation play in this
 context, we treated induced Renal Epithalial Cells
 (iRECS) with BSA, BSA-PA (Palmitic Acid), BSA-OA (Oleic
 Acid), BSA-PA/OA, BSA + DGAT1/2 inhibitors, BSA-PA + DGAT1/2
 inhibitors and BSA-PA/OA + DGAT1/2 inhibitors. 
description: iRECs treated with BSA,
 BSA-PA, BSA-OA, BSA-PA/OA, BSA + DGAT1/2 inhibitors, BSA-PA
 + DGAT1/2 inhibitors and BSA-PA/OA + DGAT1/2 inhibitors  were
 subjected to shotgun lipidomics and quantified
 <strong>Lipid extraction
 for mass spectrometry lipidomics </strong>
 Mass spectrometry-based lipid
 analysis was performed by Lipotype GmbH (Dresden, Germany) as
 described (Sampaio et al,
 2011). Lipids were
 extracted using a two-step chloroform/methanol
 procedure (Ejsing et al,
 2009). Samples were spiked
 with internal lipid standard mixture containing: cardiolipin
 14:0/14:0/14:0/14:0 (CL), ceramide 18:1;2/17:0 (Cer), diacylglycerol
 17:0/17:0 (DAG), hexosylceramide 18:1;2/12:0 (HexCer), lyso-phosphatidate
 17:0 (LPA), lyso-phosphatidylcholine 12:0 (LPC),
 lyso-phosphatidylethanolamine 17:1 (LPE), lyso-phosphatidylglycerol 17:1
 (LPG), lyso-phosphatidylinositol 17:1 (LPI), lyso-phosphatidylserine 17:1
 (LPS), phosphatidate 17:0/17:0 (PhA), phosphatidylcholine 17:0/17:0 (PC),
 phosphatidylethanolamine 17:0/17:0 (PE), phosphatidylglycerol 17:0/17:0
 (PG), phosphatidylinositol 16:0/16:0 (PI), phosphatidylserine 17:0/17:0
 (PS), cholesterol ester 20:0 (CE), sphingomyelin 18:1;2/12:0;0 (SM),
 sulfatide d18:1;2/12:0;0 (Sulf), triacylglycerol 17:0/17:0/17:0 (TAG) and
 cholesterol D6 (Chol). After extraction, the organic phase was transferred
 to an infusion plate and dried in a speed vacuum concentrator. 1st step
 dry extract was re-suspended in 7.5 mM ammonium acetate in
 chloroform/methanol/propanol (1:2:4, V:V:V) and 2nd step dry extract in
 33% ethanol solution of methylamine in chloroform/methanol (0.003:5:1;
 V:V:V). All liquid handling steps were performed using Hamilton Robotics
 STARlet robotic platform with the anti-droplet control feature for organic
 solvents pipetting. 
 <strong>MS data
 acquisition </strong> Samples were analyzed by direct infusion on a
 QExactive mass spectrometer (Thermo Scientific) equipped with a TriVersa
 NanoMate ion source (Advion Biosciences). Samples were analyzed in both
 positive and negative ion modes with a resolution of Rm/z=200=280000 for
 MS and Rm/z=200=17500 for MSMS experiments, in a single acquisition. MSMS
 was triggered by an inclusion list encompassing corresponding MS mass
 ranges scanned in 1 Da increments (Surma et al, 2015). Both MS and MSMS data were combined to monitor
 CE, DAG and TAG ions as ammonium adducts; PC, PC O-, as acetate adducts;
 and CL, PA, PE, PE O-, PG, PI and PS as deprotonated anions. MS only was
 used to monitor LPA, LPE, LPE O-, LPI and LPS as deprotonated anions; Cer,
 HexCer, SM, LPC and LPC O- as acetate adducts and cholesterol as ammonium
 adduct of an acetylated derivative (Liebisch et al, 2006).
 <strong>Data analysis
 and post-processing </strong>
 Data were analysed with
 in-house developed lipid identification software based on
 LipidXplorer (Herzog et
 al, 2012; Herzog et al, 2011). Data post-processing and normalization were
 performed using an in-house developed data management system. Only lipid
 identifications with a signal-to-noise ratio &gt;5, and a signal
 intensity 5-fold higher than in corresponding blank samples were
 considered for further data analysis.