Applying Label-Free Quantitation to Top Down Proteomics

作者:Ntai Ioanna; Kim Kyunggon; Fellers Ryan T; Skinner Owen S; Smith Archer D; Early Bryan P; Savaryn John P; LeDuc Richard D; Thomas Paul M; Kelleher Neil L*
来源:Analytical Chemistry, 2014, 86(10): 4961-4968.
DOI:10.1021/ac500395k

摘要

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 lcDa in a complex system. The input is similar to 100-400 mu g 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 Delta rpd3 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.