In silico approach to predict pancreatic β-cells classically secreted proteins
| Autor: | Per Hägglund, Celina Pihl, Tatiana Orli Milkewitz Sandberg, Michal Marzec, Erika Pinheiro-Machado |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Proteomics Proteome Bioinformatics Protein Conformation In silico Biophysics Context (language use) Computational biology Biology Biochemistry 03 medical and health sciences Mice 0302 clinical medicine Endocrinology Cell Line Tumor Insulin-Secreting Cells protein secretion medicine Animals Humans Secretion Computer Simulation Amino Acid Sequence Databases Protein Molecular Biology Secretory pathway Research Articles Conserved Sequence Diabetes & Metabolic Disorders pancreatic islets Secretory Pathway Pancreatic islets Beta cells Proteins Cell Biology Rats secretome 030104 developmental biology medicine.anatomical_structure Secretory protein Metabolism 030220 oncology & carcinogenesis UniProt |
| Zdroj: | Bioscience reports, 40(2):BSR20193708. Portland Press Bioscience Reports Pinheiro-Machado, E, Sandberg, T O M, Pihl, C, Hägglund, P M & Marzec, M T 2020, ' In silico approach to predict pancreatic β-cells classically secreted proteins ', Bioscience Reports, vol. 40, no. 2, BSR20193708 . https://doi.org/10.1042/BSR20193708 |
| ISSN: | 0144-8463 |
| DOI: | 10.1042/BSR20193708 |
| Popis: | Pancreatic β-cells, residents of the islets of Langerhans, are the unique insulin-producers in the body. Their physiology is a topic of intensive studies aiming to understand the biology of insulin production and its role in diabetes pathology. However, investigations about these cells’ subset of secreted proteins, the secretome, are surprisingly scarce and a list describing islet/β-cell secretome upon glucose-stimulation is not yet available. In silico predictions of secretomes are an interesting approach that can be employed to forecast proteins likely to be secreted. In this context, using the rationale behind classical secretion of proteins through the secretory pathway, a Python tool capable of predicting classically secreted proteins was developed. This tool was applied to different available proteomic data (human and rodent islets, isolated β-cells, β-cell secretory granules, and β-cells supernatant), filtering them in order to selectively list only classically secreted proteins. The method presented here can retrieve, organize, search and filter proteomic lists using UniProtKB as a central database. It provides analysis by overlaying different sets of information, filtering out potential contaminants and clustering the identified proteins into functional groups. A range of 70–92% of the original proteomes analyzed was reduced generating predicted secretomes. Islet and β-cell signal peptide-containing proteins, and endoplasmic reticulum-resident proteins were identified and quantified. From the predicted secretomes, exemplary conservational patterns were inferred, as well as the signaling pathways enriched within them. Such a technique proves to be an effective approach to reduce the horizon of plausible targets for drug development or biomarkers identification. |
| Databáze: | OpenAIRE |
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