Dataset Information

Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy

ABSTRACT: 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 on the ability of the cell 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 study 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 represent alsoa consistent compendium of protein half-lives in human fibroblasts and a rich source of important information related to basic cell biology.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Primary Cell, Fibroblast

DISEASE(S): Type 1 Diabetes Mellitus

SUBMITTER: Giorgio Arrigoni

LAB HEAD: Giorgio Arrigoni

PROVIDER: PXD038541 | Pride | 2023-02-13

REPOSITORIES: Pride

ACCESS DATA

Publications

Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy.

Di Camillo Barbara B Puricelli Lucia L Iori Elisabetta E Toffolo Gianna Maria GM Tessari Paolo P Arrigoni Giorgio G

International journal of molecular sciences 20230201 3

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 d ...[more]

PMID: 36769128

Similar Datasets

Project description:Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization and turnover rates, on a whole proteome level remains a major challenge in the post-genome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labelling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and SILAC, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualised using specialised software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was approximately 20 hours. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxy terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multi-protein complexes, suggesting a general mechanism whereby their assembly is controlled in a different subcellular location to their main site of function.

Dataset Information

Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy

Publications

Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure