Proteomic profiling of exosomes derived from pancreatic beta-cells cultured under hyperglycemia

Author:

Rząca Carina1,Jankowska Urszula2,Stępień Ewa Łucja3

Affiliation:

1. M. Smoluchowski Institute of Physics, Faculty of Physics, Astronomy and Applied Computer Science , Jagiellonian University , Krakow , Poland ; and Centre for Theranostics, Jagiellonian University , Kraków , Poland .

2. Proteomics and Mass Spectrometry Core Facility, Malopolska Centre of Biotechnology , Jagiellonian University, Krakow , Poland

3. Instytut Fizyki im. Mariana Smoluchowskiego , Uniwersytet Jagielloński , 11 Łojasiewicza St., 30-348 Kraków , Poland ; Total-Body Jagiellonian-PET Laboratory , Jagiellonian University , Kraków , Poland ; and Centre for Theranostics, Jagiellonian University , Kraków , Poland , Phone: +48 12 664 47 62.

Abstract

Abstract Introduction Cargo carried by extracellular vesicles (EVs) is considered a promising diagnostic marker, especially proteins. EVs can be divided according to their size and way of biogenesis into exosomes (diameter < 200 nm) and ectosomes (diameter > 200 nm). Exosomes are considered to be of endocytic origin, and ectosomes are produced by budding and shedding from the plasma membrane [1]. Methods The first step of this study was a characterization of the exosome sample. Using Tunable Resistive Pulse Sensing (qNano) size distribution and concentration were measured. The mean size of exosomes was 120±9.17 nm. In the present study, a nano liquid chromatography coupled with tandem mass spectrometry (nanoLCMS/MS) was used to compare protein profiles of exosomes secreted by pancreatic beta cells (1.1B4) grown under normal glucose (NG, 5 mM D-glucose) and high glucose (HG, 25 mM D-glucose) conditions. The EV samples were lysed, and proteins were denatured, digested, and analyzed using a Q-Exactive mass spectrometer coupled with the UltiMate 3000 RSLC nano system. The nanoLC-MS/MS data were searched against the SwissProt Homo sapiens database using MaxQuant software and protein quantitation was done by the MaxLFQ algorithm. Statistical analysis was carried out with Perseus software. Further bioinformatic analysis was performed using the FunRich 3.1.4 software with the UniProt protein database and String [2]. Results As a result of the nanoLC-MS/MS analysis more than 1,000 proteins were identified and quantified in each sample. The average number of identified proteins in exosomes was 1,397. Label-free quantitative analysis showed that exosome composition differed significantly between those isolated under NG and HG conditions. Many pathways were down-regulated in HG, particularly the ubiquitin-proteasome pathway. In addition, a significant up-regulation of the Ras-proteins pathway was observed in HG. Conclusion Our description of exosomes protein content and its related functions provides the first insight into the EV interactome and its role in glucose intolerance development and diabetic complications. The results also indicate the applicability of EV proteins for further investigation regarding their potential as circulating in vivo biomarkers.

Publisher

Walter de Gruyter GmbH

Subject

Health Informatics,Biochemistry, Genetics and Molecular Biology (miscellaneous),Medicine (miscellaneous),General Computer Science

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