Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics

Abstract

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, for example 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, for example, 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, for example, ± 0.01 Daltons. 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.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

“…For the quantitative site-specific glycoprofiling, the HCD- and EThcD-MS/MS data from File B were first searched using Byos v3.9–7 (Protein Metrics Inc.) 33 , 65 . The ‘default’ search strategy for N -glycopeptides commonly used by teams in this study was employed for the Byos search (see details below).…”

Characterization of the O-Glycoproteome of Porphyromonas gingivalis

“…All searches were conducted using trypsin with up to two missed cleavages allowed, peptide mass tolerance was set to 10 ppm, fragment mass tolerance to 0.2 Da, and a fixed modification of carbamidomethyl (C). Initially, the raw MS data were searched with Byonic v3.9.6 (Protein Metrics Inc) using the wildcard setting, initially set to 100–2000 Da and later extended to 2500 Da ( 55 ). After identification of most of the glycan additions, the data were searched again using specific modifications as follows: common modifications: oxidation (M), 1394.42 (S, T) and 1436.43 (S, T); rare modifications: 792.25 (S, T) and 1352.42 (S, T).…”

Characterization of the O-Glycoproteome of Tannerella forsythia

“…Peptide mass tolerance was set to 10 ppm and fragment mass tolerance to 0.04 Da, with a fixed modification of carbamidomethyl (C). Initially, the raw MS data was searched with Byonic v3.9.6 (Protein Metrics Inc.) using the wildcard setting, initially set to 100 to 2,000 Da and later extended to 2,500 Da ( 28 ). After identification of most of the glycan additions, the data were searched again using specific modifications as follows.…”