Open AccessCalculation of the Protein Turnover Rate Using the Number of Incorporated 2H Atoms and Proteomics Analysis of a Single Labeled Sample
Author(s) -
Serguei Ilchenko,
Andrew Haddad,
Prabodh Sadana,
Fabio A. Recchia,
Rovshan G. Sadygov,
Takhar Kasumov
Publication year - 2019
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/acs.analchem.9b02757
Subject(s) - chemistry , proteome , constant (computer programming) , reaction rate constant , biological system , sample (material) , mass spectrometry , term (time) , protein turnover , analytical chemistry (journal) , algorithm , proteomics , time point , chromatography , biochemistry , kinetics , computer science , protein biosynthesis , physics , gene , biology , quantum mechanics , acoustics , programming language
Rate constant estimation with heavy water requires a long-term experiment with data collection at multiple time points (3-4 weeks for mitochondrial proteome dynamics in mice and much longer in other species). When tissue proteins are analyzed, this approach requires euthanizing animals at each time point or multiple tissue biopsies in humans. Although short-term protocols are available, they require knowledge of the maximum number of isotope labels ( N ) and accurate quantification of observed 2 H-enrichment in the peptide. The high-resolution accurate mass spectrometers used for proteome dynamics studies are characterized by a systematic spectral error that compromises these measurements. To circumvent these issues, we developed a simple algorithm for the rate constant calculation based on a single labeled sample and comparable unlabeled (time 0) sample. The algorithm determines N for all proteogenic amino acids from a long-term experiment to calculate the predicted plateau 2 H-labeling of peptides for a short-term protocol and estimates the rate constant based on the measured baseline and the predicted plateau 2 H-labeling of peptides. The method was validated based on the rate constant estimation in a long-term experiment in mice and dogs. The improved 2 time-point method enables the rate constant calculation with less than 10% relative error compared to the bench-marked multi-point method in mice and dogs and allows us to detect diet-induced subtle changes in ApoAI turnover in mice. In conclusion, we have developed and validated a new algorithm for protein rate constant calculation based on 2-time point measurements that could also be applied to other biomolecules.