Ultraviolet Photodissociation and Activated Electron Photodetachment Mass Spectrometry for Top-Down Sequencing of Modified Oligoribonucleotides.

With the increased development of new RNA-based therapeutics, the need for robust analytical methods for confirming sequences and mapping modifications has accelerated. Characterizing modified ribonucleic acids using mass spectrometry is challenging because diagnostic fragmentation may be suppressed for modified nucleotides, thus hampering complete sequence coverage and the confident localization of modifications. Ultraviolet photodissociation (UVPD) has shown great potential for the characterization of nucleic acids due to extensive backbone fragmentation. Activated electron photodetachment dissociation (a-EPD) has also been used as an alternative to capitalize on the dominant charge-reduction pathway prevalent in UVPD, facilitate dissociation, and produce high abundances of fragment ions. Here, we compare higher-energy collisional activation (HCD), UVPD using 193 and 213 nm photons, and a-EPD for the top-down sequencing of modified nucleic acids, including methylated, phosphorothioate, and locked nucleic acid-modified DNA. The presence of these modifications alters the fragmentation pathways observed upon UVPD and a-EPD, and extensive backbone cleavage is observed that results in the production of fragment ions that retain the modifications and allow them to be pinpointed. LNA and 2'-O-methoxy phosphorothioate modifications caused a significant suppression of fragmentation for UVPD but not for a-EPD, whereas phosphorothioate bonds did not cause any significant suppression for either method. The incorporation of 2'-O-methyl modifications suppressed fragmentation of the antisense strand of patisiran, which resulted in some gaps in sequence coverage. However, UVPD provided the highest sequence coverage when compared to a-EPD.

Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics.

Glycopeptides in peptide or digested protein samples pose a number of analytical and bioinformatics challenges beyond those posed by unmodified peptides or peptides with smaller posttranslational modifications. Exact structural elucidation of glycans is generally beyond the capability of a single mass spectrometry experiment, so a reasonable level of identification for tandem mass spectrometry, taken by several glycopeptide software tools, is that of peptide sequence and glycan composition, meaning the number of monosaccharides of each distinct mass, e.g., HexNAc(2)Hex(5) rather than man5. Even at this level, however, glycopeptide analysis poses challenges: finding glycopeptide spectra when they are a tiny fraction of the total spectra; assigning spectra with unanticipated glycans, not in the initial glycan database; and finding, scoring, and labeling diagnostic peaks in tandem mass spectra. Here, we discuss recent improvements to Byonic, a glycoproteomics search program, that address these three issues. Byonic now supports filtering spectra by m/z peaks, so that the user can limit attention to spectra with diagnostic peaks, e.g., at least two out of three of 204.087 for HexNAc, 274.092 for NeuAc (with water loss), and 366.139 for HexNAc-Hex, all within a set mass tolerance, e.g., ± 0.01 Da. Also, new is glycan "wildcard" search, which allows an unspecified mass within a user-set mass range to be applied to N- or O-linked glycans and enables assignment of spectra with unanticipated glycans. Finally, the next release of Byonic supports user-specified peak annotations from user-defined posttranslational modifications. We demonstrate the utility of these new software features by finding previously unrecognized glycopeptides in publicly available data, including glycosylated neuropeptides from rat brain.