Algorithms and design strategies towards automated glycoproteomics analysis

Hu, Han; Khatri, Kshitij; Zaia, Joseph

doi:10.1002/mas.21487

Cited by 85 publications

(79 citation statements)

References 232 publications

(290 reference statements)

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“…The extent of dissociation is higher for non-resonant dissociation such as those observed in beam type (Q-TOF, triple quadrupole and HCD) dissociation than for resonant dissociation observed in trapped ion instruments. It is necessary to observe peptide backbone fragments in glycopeptide tandem MS for confident assignment of glycopeptide identity [6–8]. Because the glycopeptide ions are protonated, monosaccharide rearrangements occur [9], making assignment of glycan topologies from collisional dissociation tandem mass spectra risky.…”

Section: Introductionmentioning

confidence: 99%

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

2016

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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 copurified 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.

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Section: Introductionmentioning

confidence: 99%

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

2016

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“…Higher computational power will also lead to the development of novel bioinformatics tools for glycoproteomics. New and innovative software can allow us to quickly and accurately identify glycopeptides, especially intact glycopeptides, and to obtain more valuable information regarding protein glycosylation sites and glycan structures (Hu et al, ; Lakbub et al, ). Due to the importance and complexity of protein glycosylation, it is urgent to further develop effective chemical and enzymatic methods for global analysis of glycoproteins.…”

Section: Discussionmentioning

confidence: 99%

Global and site‐specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry

Xiao

Sun

Suttapitugsakul

et al. 2019

Mass Spectrometry Reviews

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Protein glycosylation is ubiquitous in biological systems and plays essential roles in many cellular events. Global and site‐specific analysis of glycoproteins in complex biological samples can advance our understanding of glycoprotein functions and cellular activities. However, it is extraordinarily challenging because of the low abundance of many glycoproteins and the heterogeneity of glycan structures. The emergence of mass spectrometry (MS)‐based proteomics has provided us an excellent opportunity to comprehensively study proteins and their modifications, including glycosylation. In this review, we first summarize major methods for glycopeptide/glycoprotein enrichment, followed by the chemical and enzymatic methods to generate a mass tag for glycosylation site identification. We next discuss the systematic and quantitative analysis of glycoprotein dynamics. Reversible protein glycosylation is dynamic, and systematic study of glycoprotein dynamics helps us gain insight into glycoprotein functions. The last part of this review focuses on the applications of MS‐based proteomics to study glycoproteins in different biological systems, including yeasts, plants, mice, human cells, and clinical samples. Intact glycopeptide analysis is also included in this section. Because of the importance of glycoproteins in complex biological systems, the field of glycoproteomics will continue to grow in the next decade. Innovative and effective MS‐based methods will exponentially advance glycoscience, and enable us to identify glycoproteins as effective biomarkers for disease detection and drug targets for disease treatment. © 2019 Wiley Periodicals, Inc. Mass Spec Rev 9999: XX–XX, 2019.

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“…Continuous developments of MS methods in past decades 10,20 have greatly improved the characterization of glycopeptides, but revealed shortcomings in the quantitation of their TMT-labeled counterparts. We therefore evaluated both MS2-and MS3-based approaches available on Orbitrap Tribid mass spectrometers with regard to their performance for the identification and quantitation of glycopeptides.…”

Section: Glyco-sps-ms3 For Improved Identification and Quantificationmentioning

confidence: 99%

SugarQuant: a streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics

Pan

Silbern

et al. 2020

Preprint

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Site-specific regulation of protein N-glycosylation is essential in human cells. However, accurate quantification of glycosylation sites and their individual glycan moieties in a cell-wide manner is still technically challenging. Here, we introduce SugarQuant, an integrated mass spectrometry-based pipeline comprising fast protein aggregation capture (PAC)-based sample preparation, optimized multi-notch MS3 LC-MS acquisition (Glyco-SPS-MS3) and a data-processing tool (GlycoBinder) that allows for confident, global identification and quantification of intact glycopeptides in complex biological samples. PAC greatly reduces the overall samplehandling time without compromising sensitivity. Glyco-SPS-MS3 combines high-resolution MS2 and MS3 scans, resulting in enhanced reporter signals of isobaric mass tags, improved detection of N-glycopeptide fragments, and significantly lowered interference in multiplexed quantification. GlycoBinder enables streamlined processing of Glyco-SPS-MS3 data, followed by a two-step database search which increases the identification rates of intact glycopeptides by up to 22% when compared with one-step database search strategies. SugarQuant was applied to identify and quantify more than 5,000 unique glycoforms in Burkitt's lymphoma cells, and determined complex site-specific glycosylation changes that occurred upon inhibition of fucosylation at high confidence.

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Algorithms and design strategies towards automated glycoproteomics analysis

Cited by 85 publications

References 232 publications

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

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

Global and site‐specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry

SugarQuant: a streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics

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