Optimizing protein turnover measurements in animals
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Protein turnover, or the continued synthesis and degradation of cellular proteins, is a fundamental feature of life and plays an important role in the regulation of gene expression. Moreover, protein turnover determines the trajectory of physiological processes such as growth, development, hypertrophy, and atrophy, as well as aging-related debilitations. One of our lab's major interests is to develop experimental and analytical methods to determine protein half-life in cells and tissues.
Measuring turnover rates in vivo
Mass spectrometry combined with stable isotope labeling can be used to measure protein turnover rates on a large scale. Such techniques have been most commonly applied to cell in culture, where the precursors of protein synthesis can be efficiently introduced to cells via the cell culture media. Turnover rates in adult animals can differ greatly from those in cell culture, and can range from minutes to decades. Measuring turnover rates in animals in vivo however faces additional challenges, including how best to introduce the stable isotope tracer, the delay in tracer availability across organs, and potential issues of label reutilization.
In previous work, our team has used heavy water (D2O) to tag newly synthesized proteins with deuterium at stable, non-exchangeable hydrogens. D2O is an attractive tracer for mammalian protein turnover analysis for a number of reasons. For instance, D2O has a favorable safety profile because it is non-radioactive, and is well established to be non-hazardous when administered at low doses. D2O also equilibrates quickly after enteral intake with the protein precursor pool. Finally, D2O labels virtually all peptide sequences including peptides that contain essential and non-essential amino acids.
In a prior paper published in Nature Communications, we have shown that D2O labeling can be used to compare protein half-life in normal and hypertrophic mouse hearts and identify new disease markers.
Harmonizing labeling and analytic strategies
More recently, our team has collaborated with Dr. Rob Beynon's group at the University of Liverpool to perform a controlled comparison of heavy water vs amino acid labeling for measuring protein turnover rates across four different tissues (heart, liver, kidney, muscle) in the mouse. Amino acid labeling is commonly used as a metabolic protein precursor in animal models to measure in vivo protein turnover rate, but there are usually delays in how fast the labeled amino acid precursors become available for protein synthesis. This difference is likely dependent on the metabolism of the tissue too, and will delay the label incorporation into the measured protein, especially for proteins with very short half-life. We compared different kinetic models, and methods to derive the precursor kinetic parameters used to adjust half-life measurement, and compared the result to heavy water labeling which does not suffer from the same precursor delay problem. After some method refinement, we were able to show that both methods produced similar turnover rates. We provide some guidelines and best practice for correcting for precursor kinetics. We also describe an original Pythons software, Riana, which can be used to perform mass spectrometry data integration and kinetics curve fitting for both amino acid and heavy water studies. For details, please see our paper published in Molecular & Cellular Proteomics.