Liver mitochondrial proteome dataset from a rat model of streptozotocin-induced diabetes

Read full text
Authors: Jakub Stepanovsky, Natália Andelová, Aneta Čináková, Eva Kralova, Miroslav Ferko, Karol Ondriaš, Marian Grman, Anton Mišák, Lenka Tomášová
Cited by: 0

Abstract

This datasets contains data obtained from proteomic analysis of mitochondrial fractions isolated from rat liver samples. The analysis was performed using a Nano System liquid chromatograph (Ultimate 3000 RSLC, Thermo Fisher Scientific, Germering, Germany) coupled with mass spectrometry (LC–MS) using electrospray ionization (ESI) and a 3D ion trap mass analyzer (Amazon SL, Bruker, Bremen, Germany). The study was conducted on 3-month-old male spontaneously hypertensive rats (SHR, n = 6) and 3-month-old male Wistar rats (n = 6), which served as the Control group. Experimental type 1 diabetes mellitus (T1DM) was induced in SHR rats by a single intraperitoneal injection of streptozotocin (STZ; 55 mg/kg), creating the SHR-STZ group. Mitochondria were isolated from the livers of spontaneously hypertensive rats six weeks after the induction of diabetes by STZ administration. These data support a forthcoming manuscript investigating mitochondrial ferroptotic pathways in an experimental model of diabetic liver. Methods Liver mitochondria were isolated from experimental animals using standard differential centrifugation procedures. Mitochondrial protein samples were subjected to proteomic analysis using nano-liquid chromatography coupled with electrospray ionization mass spectrometry (LC-MS). Peptide separation was performed on an Ultimate 3000 RSLC system (Thermo Fisher Scientific), followed by mass spectrometric detection using an Amazon SL 3D ion trap mass spectrometer (Bruker). The resulting spectra were processed for protein identification and downstream proteomic analysis.

Fields of Study & Subjects

Advanced Proteomics Techniques and Applications Mitochondrial Function and Pathology Ferroptosis and cancer prognosis

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 March 2026
Language
EN
Document type
Dataset