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The ability to map combinatorial patterns of post-translational modifications (PTMs) of proteins remains challenging for traditional bottom-up mass spectrometry workflows. There are also hurdles associated with top-down approaches related to limited data analysis options for heavily modified proteoforms. These shortcomings have accelerated interest in middle-down MS methods that focus on analysis of large peptides generated by specific proteases in conjunction with validated bioinformatics strategies to allow quantification of isomeric histoforms. Mapping multiple PTMs simultaneously requires the ability to obtain high sequence coverage to allow confident localization of the modifications, and 193 nm ultraviolet photodissociation (UVPD) has been shown to cause extensive fragmentation for large peptides and proteins. Histones are an ideal system to test the ability of UVPD to characterize multiple modifications, as the combinations of PTMs are the underpinning of the biological significance of histones and at the same time create an imposing challenge for characterization. The present study focuses on applying 193 nm UVPD to the identification and localization of PTMs on histones by UVPD and comparison to a popular alternative, electron-transfer dissociation (ETD), via a high-throughput middle-down LC/MS/MS strategy. Histone Coder and IsoScale, bioinformatics tools for verification of PTM assignments and quantification of histone peptides, were adapted for UVPD data and applied in the present study. In total, over 300 modified forms were identified, and the distributions of PTMs were quantified between UVPD and ETD. Significant differences in patterns of PTMs were found for histones from HeLa cells prior to and after treatment with a deacetylase inhibitor. Additional fragment ion types generated by UVPD proved essential for extensive characterization of the most heavily modified forms (&gt;5 PTMs).

Extensive Characterization of Heavily Modified Histone Tails by 193 nm Ultraviolet Photodissociation Mass Spectrometry via a Middle–Down Strategy