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Spatially resolved mapping of proteome turnover dynamics with subcellular precision
Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632371/ https://www.ncbi.nlm.nih.gov/pubmed/37940635 http://dx.doi.org/10.1038/s41467-023-42861-8 |
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author | Yuan, Feng Li, Yi Zhou, Xinyue Meng, Peiyuan Zou, Peng |
author_facet | Yuan, Feng Li, Yi Zhou, Xinyue Meng, Peiyuan Zou, Peng |
author_sort | Yuan, Feng |
collection | PubMed |
description | Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions. |
format | Online Article Text |
id | pubmed-10632371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106323712023-11-10 Spatially resolved mapping of proteome turnover dynamics with subcellular precision Yuan, Feng Li, Yi Zhou, Xinyue Meng, Peiyuan Zou, Peng Nat Commun Article Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions. Nature Publishing Group UK 2023-11-08 /pmc/articles/PMC10632371/ /pubmed/37940635 http://dx.doi.org/10.1038/s41467-023-42861-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yuan, Feng Li, Yi Zhou, Xinyue Meng, Peiyuan Zou, Peng Spatially resolved mapping of proteome turnover dynamics with subcellular precision |
title | Spatially resolved mapping of proteome turnover dynamics with subcellular precision |
title_full | Spatially resolved mapping of proteome turnover dynamics with subcellular precision |
title_fullStr | Spatially resolved mapping of proteome turnover dynamics with subcellular precision |
title_full_unstemmed | Spatially resolved mapping of proteome turnover dynamics with subcellular precision |
title_short | Spatially resolved mapping of proteome turnover dynamics with subcellular precision |
title_sort | spatially resolved mapping of proteome turnover dynamics with subcellular precision |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632371/ https://www.ncbi.nlm.nih.gov/pubmed/37940635 http://dx.doi.org/10.1038/s41467-023-42861-8 |
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