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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...

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Autores principales: Di Camillo, Barbara, Puricelli, Lucia, Iori, Elisabetta, Toffolo, Gianna Maria, Tessari, Paolo, Arrigoni, Giorgio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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.
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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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