Dataset Information

Proteomic Analysis of Mouse Liver Microsomes by 2D-LC-MSMS

ABSTRACT: Liver plays a crucial role in numerous metabolic processes and therefore is the primary target of study in drug discovery and molecular toxicology. Devising an appropriate analytical strategy for an efficient analysis of the liver samples has been a major concern in proteomics. The aim of this study was to develop an LC-MS based analytical method for identification of liver proteins with adequate peptide-level confidence and protein sequence coverage. The present dataset will improve the existing knowledge on the proteins identified in mouse liver microsomes.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Hepatocyte, Liver

DISEASE(S): Disease Free

SUBMITTER: Lekha Sleno

LAB HEAD: Lekha Sleno

PROVIDER: PXD000731 | Pride | 2015-03-26

REPOSITORIES: Pride

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Dataset from proteomic analysis of rat, mouse, and human liver microsomes and S9 fractions.

Golizeh Makan M Schneider Christina C Ohlund Leanne B LB Sleno Lekha L

Data in brief 20150224

Rat, mouse and human liver microsomes and S9 fractions were analyzed using an optimized method combining ion exchange fractionation of digested peptides, and ultra-high performance liquid chromatography (UHPLC) coupled to high resolution tandem mass spectrometry (HR-MS/MS). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (Vizcaíno et al., 2013 [1]) with the dataset identifier ...[more]

PMID: 26217725

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Project description:This study used untargeted proteomics to compare blood proteomic profiles in two groups of adults that differed widely in lifestyle habits. The goal was to identify a core list of proteins that were either upregulated or downregulated based on adherence to recommended lifestyle habits in adults. A total of 52 subjects in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females) participated in this cross-sectional study. Age, education level, marital status, and height did not differ significantly between LIFE and CON groups. The LIFE and CON groups differed markedly in body composition and fat mass-related anthropometric measurements including waist circumference, body mass index (BMI), sagittal abdominal diameter (SAD), and body composition (body fat percentage and fat mass index or FMI) (p<0.001). LIFE and CON groups were also widely disparate in physical activity patterns and maximal aerobic fitness, dietary intake patterns, disease risk factor prevalence, blood measures of inflammation, triglycerides, HDL-cholesterol, glucose, and insulin, weight-adjusted leg/back and handgrip strength, and mood states. The proteomics analysis showed strong group differences for 39 of 725 proteins identified in the dried blood spot samples. Of these, 18 were downregulated in the LIFE group and collectively indicated a lower innate immune activation signature. A total of 21 proteins were upregulated in the LIFE group and supported greater lipoprotein metabolism and HDL remodeling. Lifestyle-related habits and biomarkers were probed and the variance (>50%) in downregulated and upregulated proteins was best explained by group contrasts in indicators of body composition and visceral fat including FMI and SAD. This cross-sectional study established that a relatively small number of upregulated and downregulated proteins are associated with good lifestyle habits. A targeted “lifestyle” proteomic panel based on these data could be used in future studies to determine the efficacy of various prevention and treatment strategies.

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