A mass spectrometry workflow for measuring protein turnover rates in vivo

Nat Protoc. 2019 Dec;14(12):3333-3365. doi: 10.1038/s41596-019-0222-y. Epub 2019 Nov 4.


Proteins are continually produced and degraded, to avoid the accumulation of old or damaged molecules and to maintain the efficiency of physiological processes. Despite its importance, protein turnover has been difficult to measure in vivo. Previous approaches to evaluating turnover in vivo have required custom labeling approaches, involved complex mass spectrometry (MS) analyses, or used comparative strategies that do not allow direct quantitative measurements. Here, we describe a robust protocol for quantitative proteome turnover analysis in mice that is based on a commercially available diet for stable isotope labeling of amino acids in mammals (SILAM). We start by discussing fundamental concepts of protein turnover, including different methodological approaches. We then cover in detail the practical aspects of metabolic labeling and explain both the experimental and computational steps that must be taken to obtain accurate in vivo results. Finally, we present a simple experimental workflow that enables measurement of precise turnover rates in a time frame of ~4-5 weeks, including the labeling time. We also provide all the scripts needed for the interpretation of the MS results and for comparing turnover across different conditions. Overall, the workflow presented here comprises several improvements in the determination of protein lifetimes with respect to other available methods, including a minimally invasive labeling strategy and a robust interpretation of MS results, thus enhancing reproducibility across laboratories.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acids / metabolism
  • Animals
  • Isotope Labeling / methods
  • Male
  • Mass Spectrometry / methods*
  • Mice
  • Mice, Inbred C57BL
  • Protein Biosynthesis / physiology
  • Proteins / metabolism
  • Proteolysis
  • Proteome / analysis*
  • Proteome / metabolism
  • Proteomics / methods*
  • Reproducibility of Results
  • Workflow


  • Amino Acids
  • Proteins
  • Proteome