Metalloproteomic and differential expression in plasma in a rat model of type 1 diabetes

• Autor(a) principal: Pereira Braga, Camila [UNESP]
• Data de Publicação: 2017
• Outros Autores: Cavalcante Souza Vieira, José [UNESP], Lima Leite, Aline de, Henrique Fernandes, Ana Angélica [UNESP], Rabelo Buzalaf, Marília Afonso, Magalhães Padilha, Pedro de [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.ijbiomac.2017.06.032; http://hdl.handle.net/11449/174767
• topic: Differential proteomic; Metalloproteomic; Type 1 diabetes

Type 1 diabetes is characterized by hyperglycemia, which in the chronic stage is associated with abnormalities in lipids, protein and, carbohydrate metabolism, as well as oxidative stress. New strategies for prevention and treatment are needed, as type 1 diabetes affects life quality and survival, and involves high-cost treatment. Proteomic and metalloproteomic studies can elucidate the functional and physiological aspects of biomolecules. In the present study, differential proteomics was used to identify potential biomarkers of diabetes in rat plasma associated with copper, selenium, zinc, and magnesium fractionation in control and diabetic rats, as well as diabetic rats treated with insulin. 2D-PAGE was used in the plasma protein fractionation; graphite furnace atomic absorption spectrometry (GFAAS) and flame atomic absorption spectrometry (FAAS) were used for quantitative determination of copper, magnesium, selenium, and zinc in the spots that showed different expression; and protein spots were characterized by electrospray ionization-tandem mass spectrometry (ESI–MS/MS) after tryptic digestion. ESI–MS/MS analysis characterized 35 different proteins, indicating alpha-1-macroglobulin and haptoglobulin as potential candidates as biomarkers for diabetes treated with insulin; also, 2′-deoxynucleoside 5′-phosphate N-hydrolase 1, transmembrane protein 11, serum amyloid P component, vitamin D-binding protein, and biliverdin reductase were identified as potential candidates as biomarkers for uncontrolled diabetes.