Top-down characterization of histone H4 proteoforms with ProteinGoggle 2.0

Abstract

Top-down characterization of combinatorial and dense post-translational modifications (PTMs) on core histones has long been a big analytical challenge because of enormous putative proteoforms for identification and simultaneously enormous putative sites of each individual PTM for localization. ProteinGoggle 2.0, as implemented with the isotopic mass-to-charge ratio and envelope fingerprinting algorithm, has multiple unique strengths for top-down characterization of histone PTMs together with high-resolution tandem mass spectrometry. Here we report our database search and proteoform identification of HeLa core histone H4 using ProteinGoggle 2.0. The Theoretical database containing all putative proteoforms was created with shotgun annotation from the human H4 flat text downloaded from UniProt; information including the amino acid sequence, putative PTMs (methylation, di-methylation, tri-methylation, acetylation and phosphorylation) and amino acid variation (A77 to P) was adopted from the flat text file. A total of 426 proteoforms were confidently identified with a spectrum level false discovery rate of less than 1%, which represents the most comprehensive H4 proteoforms reported so far. Side-by-side comparison of these proteoforms with those identified by ProSightPC 2.0 was also made. By and large, ProteinGoggle 2.0 can be adopted for database search and proteoform identification of proteins with multiple combinatorial PTMs as well as amino acid variation.