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Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy
Protein turnover rate is finely regulated through intracellular mechanisms and signals that are still incompletely understood but that are essential for the correct function of cellular processes. Indeed, a dysfunctional proteostasis often impacts the cell’s ability to remove unfolded, misfolded, de...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917874/ https://www.ncbi.nlm.nih.gov/pubmed/36769128 http://dx.doi.org/10.3390/ijms24032811 |
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author | Di Camillo, Barbara Puricelli, Lucia Iori, Elisabetta Toffolo, Gianna Maria Tessari, Paolo Arrigoni, Giorgio |
author_facet | Di Camillo, Barbara Puricelli, Lucia Iori, Elisabetta Toffolo, Gianna Maria Tessari, Paolo Arrigoni, Giorgio |
author_sort | Di Camillo, Barbara |
collection | PubMed |
description | Protein turnover rate is finely regulated through intracellular mechanisms and signals that are still incompletely understood but that are essential for the correct function of cellular processes. Indeed, a dysfunctional proteostasis often impacts the cell’s ability to remove unfolded, misfolded, degraded, non-functional, or damaged proteins. Thus, altered cellular mechanisms controlling protein turnover impinge on the pathophysiology of many diseases, making the study of protein synthesis and degradation rates an important step for a more comprehensive understanding of these pathologies. In this manuscript, we describe the application of a dynamic-SILAC approach to study the turnover rate and the abundance of proteins in a cellular model of diabetic nephropathy. We estimated protein half-lives and relative abundance for thousands of proteins, several of which are characterized by either an altered turnover rate or altered abundance between diabetic nephropathic subjects and diabetic controls. Many of these proteins were previously shown to be related to diabetic complications and represent therefore, possible biomarkers or therapeutic targets. Beside the aspects strictly related to the pathological condition, our data also represent a consistent compendium of protein half-lives in human fibroblasts and a rich source of important information related to basic cell biology. |
format | Online Article Text |
id | pubmed-9917874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99178742023-02-11 Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy Di Camillo, Barbara Puricelli, Lucia Iori, Elisabetta Toffolo, Gianna Maria Tessari, Paolo Arrigoni, Giorgio Int J Mol Sci Article Protein turnover rate is finely regulated through intracellular mechanisms and signals that are still incompletely understood but that are essential for the correct function of cellular processes. Indeed, a dysfunctional proteostasis often impacts the cell’s ability to remove unfolded, misfolded, degraded, non-functional, or damaged proteins. Thus, altered cellular mechanisms controlling protein turnover impinge on the pathophysiology of many diseases, making the study of protein synthesis and degradation rates an important step for a more comprehensive understanding of these pathologies. In this manuscript, we describe the application of a dynamic-SILAC approach to study the turnover rate and the abundance of proteins in a cellular model of diabetic nephropathy. We estimated protein half-lives and relative abundance for thousands of proteins, several of which are characterized by either an altered turnover rate or altered abundance between diabetic nephropathic subjects and diabetic controls. Many of these proteins were previously shown to be related to diabetic complications and represent therefore, possible biomarkers or therapeutic targets. Beside the aspects strictly related to the pathological condition, our data also represent a consistent compendium of protein half-lives in human fibroblasts and a rich source of important information related to basic cell biology. MDPI 2023-02-01 /pmc/articles/PMC9917874/ /pubmed/36769128 http://dx.doi.org/10.3390/ijms24032811 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Di Camillo, Barbara Puricelli, Lucia Iori, Elisabetta Toffolo, Gianna Maria Tessari, Paolo Arrigoni, Giorgio Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy |
title | Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy |
title_full | Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy |
title_fullStr | Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy |
title_full_unstemmed | Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy |
title_short | Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy |
title_sort | modeling silac data to assess protein turnover in a cellular model of diabetic nephropathy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917874/ https://www.ncbi.nlm.nih.gov/pubmed/36769128 http://dx.doi.org/10.3390/ijms24032811 |
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