Use of an informed search space maximizes confidence of site-specific assignment of glycoprotein glycosylation

Abstract

In order to interpret glycopeptide tandem mass spectra, it is necessary to estimate the theoretical glycan compositions and peptide sequences, known as the search space. The simplest way to do this is to build a naïve search space from sets of glycan compositions from public databases and to assume that the target glycoprotein is pure. Often, however, purified glycoproteins contain co-purified glycoprotein contaminants that have the potential to confound assignment of tandem mass spectra based on naïve assumptions. In addition, there is increasing need to characterize glycopeptides from complex biological mixtures. Fortunately, liquid chromatography-mass spectrometry (LC-MS) methods for glycomics and proteomics are now mature and accessible. We demonstrate the value of using an informed search space built from measured glycomes and proteomes to define the search space for interpretation of glycoproteomics data. We show this using α-1-acid glycoprotein (AGP) mixed into a set of increasingly complex matrices. As the mixture complexity increases, the naïve search space balloons and the ability to assign glycopeptides with acceptable confidence diminishes. In addition, it is not possible to identify glycopeptides not foreseen as part of the naïve search space. A search space built from released glycan glycomics and proteomics data is smaller than its naïve counterpart while including the full range of proteins detected in the mixture. This maximizes the ability to assign glycopeptide tandem mass spectra with confidence. As the mixture complexity increases, the number of tandem mass spectra per glycopeptide precursor ion decreases, resulting in lower overall scores and reduced depth of coverage for the target glycoprotein. We suggest use of α-1-acid glycoprotein as a standard to gauge effectiveness of analytical methods and bioinformatics search parameters for glycoproteomics studies. Graphical Abstract Assignment of site specific glycosylation from LC-tandemMS data.

Keywords: Alpha-1-acid glycoprotein; Glycoinformatics; Glycomics; Glycoproteomics; Glycosylation; Integrated-omics; Mass spectrometry.

Fig. 1

a Venn diagram showing number and overlap of proteins identified from proteomics analyses of individual serum glycoproteins and albumin and IgG depleted serum. Only proteins identified at a 1 % FDR with two or more unique peptides were included. Comparison of a naïve search space (b) with proteomics informed (c) and proteomics + glycomics informed (d) search spaces for glycoprotein mixture 3. x-axes show the Swissprot identifiers for glycoproteins included in the hypotheses and y-axis shows number of glycopeptides per glycoprotein considered. Glycoprotein standards AGP (A1AG), fetuin (FETUA), and transferrin (TRFE) are shown on the left-most side of the x-axes

Fig. 2

Base peak chromatogram of enriched transferrin glycopeptides stacked over extracted ion chromatograms for saccharide oxonium ions, generated by MS/MS, indicating the presence of glycopeptides in the eluting peaks

Fig. 3

Comparison of the performance of naïve versus informed search spaces for an AGP glycoproteomics result. a Number of glycopeptide matches over a range of confidence thresholds (q-value) based on glycoproteomics searches followed by FDR calculation by decoy database searches. Colored lines represent different hypotheses as indicated in the legend. b A comparison of number of glycopeptides and decoys matches for naïve and informed search spaces at different MS² score thresholds

Fig. 4

Effects of increasing sample complexity on analytical methods. a Base peak chromatograms (MS only) for samples with different levels of complexity. b Extracted ion chromatograms showing the abundance of an AGP glycopeptide (LVPVPITNATLDR-Hex₆, HexNAc₅, NeuAc₃) in the different complexity levels. c The average number of tandem mass spectra acquired per precursor across samples of different complexity. d Distributions of precursors selected for tandem MS across a LC-tandem MS experiment for samples with scaling complexity levels

Fig. 5

Grouped bar plots showing identified site-specific AGP glycoforms in samples of different complexity levels and depleted serum. The different glycoforms for each glycosylation site are listed on the x-axes while the y-axes indicate summed abundances of all fragment ions in the matched glycopeptide spectra. Different colored bars are specific for pure AGP, glycoprotein mixtures, or depleted serum as indicated in the legend