Raw proteomic dataset of prostatic tissue and seminal vesicle fluid from obese, diabetic and control rats

Description

Study question: Can obesity and diabetes induced in male rodents alter the proteome of prostatic tissue and seminal vesicle fluid? The data presented reflect the proteomic profile of prostatic tissue and seminal vesicle fluid from male Wistar rats, distributed into three groups: control, obese, and diabetic. The rats were fed with commercially available chow provided in a controlled manner for the control and diabetic groups, while the obese group received a high-calorie diet with 5% sucrose added to the water, provided ad libitum, for 38 weeks. Diabetes was induced through an injection of streptozotocin (35 mg/kg), 53 days prior to euthanasia. After euthanasia, the prostatic tissues and seminal vesicles (fluids) were dissected, and the samples were homogenized with RIPA buffer containing protease inhibitors. The samples were then subjected to sonication, centrifugation, and the resulting supernatant was used for total protein quantification. Trypsin digestion was performed in-gel, and the prepared samples were analyzed individually by mass spectrometry, with proteomics conducted using a shotgun approach. The data can be interpreted as follows: there are two folders in the dataset, separated for prostatic tissue and seminal vesicle fluid, divided by control, diabetic, and obese groups, containing all the proteins quantified by animal, properly identified. For each biological sample, there is an Excel spreadsheet with the normalized proteomic data.

Steps to reproduce

Spectra were acquired with MassLynx v.4.1 software, and raw data files were converted to peak list (.mgf) format and searched against the UniprotSProt 10116 database for Rattus norvegicus using Mascot 2.3.02 and Mascot Distiller MDRO 2.4.0.0. Protein quantification was determined using the exponentially modified protein abundance index (emPAI). Gene ontology (GO) annotations were obtained using ShinyGO 0.75 online software, focusing on the molecular function category. The data were analyzed using non-hierarchical clustering with MetaboAnalyst software. To confirm group divisions and assess the impact of outliers, principal component analysis (PCA) was used. A heatmap was created for visual protein comparison across groups. Univariate analysis (ANOVA) and Fisher LSD test were applied for multiple comparisons, with significance set at FDR < 0.05. The ROC curve was constructed for prostate tissue and seminal vesicle fluid, comparing the treated groups (diabetic or obese) to the control group, with significance defined as AUC > 0.80 and P < 0.05.

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