Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants

Protein
turnover is an important aspect of the regulation of cellular
processes for organisms when responding to developmental or environmental
cues. The measurement of protein turnover in plants, in contrast to
that of rapidly growing unicellular organismal cultures, is made more
complicated by the high degree of amino acid recycling, resulting
in significant transient isotope incorporation distributions that
must be dealt with computationally for high throughput analysis to
be practical. An algorithm in R, ProteinTurnover, was developed to
calculate protein turnover with transient stable isotope incorporation
distributions in a high throughput automated manner using high resolution
MS and MS/MS proteomic analysis of stable isotopically labeled plant
material. ProteinTurnover extracts isotopic distribution information
from raw MS data for peptides identified by MS/MS from data sets of
either isotopic label dilution or incorporation experiments. Variable
isotopic incorporation distributions were modeled using binomial and
beta-binomial distributions to deconvolute the natural abundance,
newly synthesized/partial-labeled, and fully labeled peptide distributions.
Maximum likelihood estimation was performed to calculate the distribution
abundance proportion of old and newly synthesized peptides. The half-life
or turnover rate of each peptide was calculated from changes in the
distribution abundance proportions using nonlinear regression. We
applied ProteinTurnover to obtain half-lives of proteins from enriched
soluble and membrane fractions from Arabidopsis roots.