JUMPt: Comprehensive Protein Turnover Modeling of In Vivo Pulse SILAC Data by Ordinary Differential Equations

Recent
advances in mass spectrometry (MS)-based proteomics allow
the measurement of turnover rates of thousands of proteins using dynamic
labeling methods, such as pulse stable isotope labeling by amino acids
in cell culture (pSILAC). However, when applying the pSILAC strategy
to multicellular animals (e.g., mice), the labeling process is significantly
delayed by native amino acids recycled from protein degradation in
vivo, raising a challenge of defining accurate protein turnover rates.
Here, we report JUMPt, a software package using a novel ordinary differential
equation (ODE)-based mathematical model to determine reliable rates
of protein degradation. The uniqueness of JUMPt is to consider amino
acid recycling and fit the kinetics of the labeling amino acid (e.g.,
Lys) and whole proteome simultaneously to derive half-lives of individual
proteins. Multiple settings in the software are designed to enable
simple to comprehensive data inputs for precise analysis of half-lives
with flexibility. We examined the software by studying the turnover
of thousands of proteins in the pSILAC brain and liver tissues. The
results were largely consistent with the proteome turnover measurements
from previous studies. The long-lived proteins are enriched in the
integral membrane, myelin sheath, and mitochondrion in the brain.
In summary, the ODE-based JUMPt software is an effective proteomics
tool for analyzing large-scale protein turnover, and the software
is publicly available on GitHub (https://github.com/JUMPSuite/JUMPt) to the research community.