Applying label-free quantitation to top down proteomics

将无标记定量技术应用于自上而下的蛋白质组学

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作者:Ioanna Ntai, Kyunggon Kim, Ryan T Fellers, Owen S Skinner, Archer D Smith 4th, Bryan P Early, John P Savaryn, Richard D LeDuc, Paul M Thomas, Neil L Kelleher

Abstract

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.

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