Proteome Birthdating: A Single-Sample Approach for Measuring Global Turnover Dynamics and “Protein Age”

Within a cell, proteins have distinct and highly variable half-lives. As a result, the molecular ages of proteins can range from seconds to years. How the age of a protein influences its environmental interactions is a largely unexplored area of biology. To facilitate such studies, we recently developed a technique termed "proteome birthdating" that differentially labels proteins based on their time of synthesis. Proteome birthdating enables analyses of age distributions of the proteome by tandem mass spectrometry (LC-MS/MS) and provides a methodology for investigating the protein age selectivity of diverse cellular pathways. Proteome birthdating can also provide measurements of protein turnover kinetics from single, sequentially labeled samples. Here, we provide a practical guide for conducting proteome birthdating in in vitro model systems. The outlined workflow covers cell culture, isotopic labeling, protein extraction, enzymatic digestion, peptide cleanup, mass spectrometry, data processing, and theoretical considerations for interpretation of the resulting data. Key features • Proteome birthdating barcodes the proteome with isotopically labeled precursors based on time of synthesis or "age." • Global protein turnover kinetics can be analyzed from single, sequentially labeled biological samples. • Protein age distributions of subsets of the proteome can be analyzed (e.g., ubiquitinated proteins). • Age selectivity of protein properties, cellular pathways, or disease states can be investigated.

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Publication Details

Journal
BIO-PROTOCOL
Published
2025-01-01
DOI
https://doi.org/10.21769/bioprotoc.5296
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Proteome Birthdating: A Single-Sample Approach for Measuring Global Turnover Dynamics and “Protein Age”

M.W. Ahmed, Sina Ghaemmaghami, Fatemeh Alimohammadi, Margaret Hoare et al.
BIO-PROTOCOL
Advanced Proteomics Techniques and Applications
article

Proteome Birthdating: A Single-Sample Approach for Measuring Global Turnover Dynamics and “Protein Age”

M.W. Ahmed, Sina Ghaemmaghami, Fatemeh Alimohammadi, Margaret Hoare, Abigail Buchwalter, Vera Gorbunova, Kyle Swovick, Kevin A. Welle, Michael E. Meadow, Andrei Seluanov, Ankur Jain, Sarah Broas, Jennifer R. Hryhorenko, John C Martinez
article en

Abstract

Within a cell, proteins have distinct and highly variable half-lives. As a result, the molecular ages of proteins can range from seconds to years. How the age of a protein influences its environmental interactions is a largely unexplored area of biology. To facilitate such studies, we recently developed a technique termed "proteome birthdating" that differentially labels proteins based on their time of synthesis. Proteome birthdating enables analyses of age distributions of the proteome by tandem mass spectrometry (LC-MS/MS) and provides a methodology for investigating the protein age selectivity of diverse cellular pathways. Proteome birthdating can also provide measurements of protein turnover kinetics from single, sequentially labeled samples. Here, we provide a practical guide for conducting proteome birthdating in in vitro model systems. The outlined workflow covers cell culture, isotopic labeling, protein extraction, enzymatic digestion, peptide cleanup, mass spectrometry, data processing, and theoretical considerations for interpretation of the resulting data. Key features • Proteome birthdating barcodes the proteome with isotopically labeled precursors based on time of synthesis or "age." • Global protein turnover kinetics can be analyzed from single, sequentially labeled biological samples. • Protein age distributions of subsets of the proteome can be analyzed (e.g., ubiquitinated proteins). • Age selectivity of protein properties, cellular pathways, or disease states can be investigated.

BIO-PROTOCOLVol. 15(1370)
University of California, San Francisco (US), University of Rochester Medical Center (US), University of Rochester (US)
Openalex Percentile: Top 92%
Advanced Proteomics Techniques and Applications
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