Applying Label-Free Quantitation to Top Down Proteomics

With
the prospect of resolving whole protein molecules into their
myriad proteoforms on a proteomic scale, the question of their quantitative
analysis in discovery mode comes to the fore. Here, we demonstrate
a robust pipeline for the identification and stringent scoring of
abundance changes of whole protein forms <30 kDa in a complex system.
The input is ∼100–400 μg of total protein for
each biological replicate, and the outputs are graphical displays
depicting statistical confidence metrics for each proteoform (i.e., a volcano plot and representations of the technical
and biological variation). A key part of the pipeline is the hierarchical
linear model that is tailored to the original design of the study.
Here, we apply this new pipeline to measure the proteoform-level effects
of deleting a histone deacetylase (rpd3) in S. cerevisiae. Over 100 proteoform changes were detected
above a 5% false positive threshold in WT vs the Δrpd3 mutant, including the validating observation of hyperacetylation
of histone H4 and both H2B isoforms. Ultimately, this approach to
label-free top down proteomics in discovery mode is a critical technical
advance for testing the hypothesis that whole proteoforms can link
more tightly to complex phenotypes in cell and disease biology than
do peptides created in shotgun proteomics.