Improved Method to Determine Protein Turnover Rates with Heavy Water Labeling by Mass Isotopomer Ratio Selection.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Jordan Currie, Dominic C M Ng, Boomathi Pandi, Alexander Black, Vyshnavi Manda, Cheyanne Durham, Jay Pavelka, Maggie P Y Lam, Edward Lau
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Abstract

The synthesis and degradation rates of proteins form an essential component of gene expression control. Heavy water labeling has been used in conjunction with mass spectrometry to measure protein turnover rates, but the optimal analytical approaches to derive turnover rates from the mass isotopomer patterns of deuterium-labeled peptides continue to be a subject of research. Here, we describe a method that comprises (1) a nearest lookup of numerically approximated peptide isotope envelopes, coupled to (2) the selection of optimal mass isotopomer pairs based on peptide sequence rules, to calculate the molar fraction of new peptide synthesis in heavy water labeling mass spectrometry experiments. We validated our approach using an experimental calibration standard comprising mixtures of fully unlabeled and fully labeled proteomes. We then reanalyzed 17 proteome-wide turnover experiments from four mouse organs across multiple data sets and showed that the combined nearest-lookup and rule-based mass isotopomer ratio selection method increases the coverage of well-fitted peptides in protein turnover experiments by up to 58 ± 13%. The workflow is implemented in the Riana software tool for protein turnover analysis and may avail ongoing efforts to study the synthesis and degradation kinetics of proteins in animals on a proteome-wide scale.

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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
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