Protein kinetic signatures of the remodeling heart following isoproterenol stimulation
Protein temporal dynamics play a critical role in time-dimensional pathophysiological processes, including the gradual cardiac remodeling that occurs in early-stage heart failure. Methods for quantitative assessments of protein kinetics are lacking, and despite knowledge gained from single-protein s...
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Published in: | The Journal of clinical investigation Vol. 124; no. 4; pp. 1734 - 1744 |
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Main Authors: | , , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
American Society for Clinical Investigation
01-04-2014
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Subjects: | |
Online Access: | Get full text |
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Summary: | Protein temporal dynamics play a critical role in time-dimensional pathophysiological processes, including the gradual cardiac remodeling that occurs in early-stage heart failure. Methods for quantitative assessments of protein kinetics are lacking, and despite knowledge gained from single-protein studies, integrative views of the coordinated behavior of multiple proteins in cardiac remodeling are scarce. Here, we developed a workflow that integrates deuterium oxide (2H2O) labeling, high-resolution mass spectrometry (MS), and custom computational methods to systematically interrogate in vivo protein turnover. Using this workflow, we characterized the in vivo turnover kinetics of 2,964 proteins in a mouse model of β-adrenergic-induced cardiac remodeling. The data provided a quantitative and longitudinal view of cardiac remodeling at the molecular level, revealing widespread kinetic regulations in calcium signaling, metabolism, proteostasis, and mitochondrial dynamics. We translated the workflow to human studies, creating a reference dataset of 496 plasma protein turnover rates from 4 healthy adults. The approach is applicable to short, minimal label enrichment and can be performed on as little as a single biopsy, thereby overcoming critical obstacles to clinical investigations. The protein turnover quantitation experiments and computational workflow described here should be widely applicable to large-scale biomolecular investigations of human disease mechanisms with a temporal perspective. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 Authorship note: Maggie P.Y. Lam, Ding Wang, Edward Lau, and David A. Liem contributed equally to this work. |
ISSN: | 0021-9738 1558-8238 |
DOI: | 10.1172/jci73787 |