Next-generation site-specific N-glycoproteomics using CustomGlyco tomato
Ontology highlight
ABSTRACT:
ORGANISM(S): Solanum Lycopersicum
SUBMITTER: 
Xiaoyong Zhao
PROVIDER: PXD059300 | iProX | Mon Dec 30 00:00:00 GMT 2024
REPOSITORIES: iProX
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Project description:Regulation of protein N-glycosylation is essential in human cells. However, large-scale, accurate, and site-specific quantification of glycosylation is still technically challenging. We here introduce SugarQuant, an integrated mass spectrometry-based pipeline comprising protein aggregation capture (PAC)-based sample preparation, multi-notch MS3 acquisition (Glyco-SPS-MS3) and a data-processing tool (GlycoBinder) that enables confident identification and quantification of intact glycopeptides in complex biological samples. PAC significantly reduces sample-handling 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 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 glycopeptides by 22% compared with conventional strategies. We apply SugarQuant to identify and quantify more than 5,000 unique glycoforms in Burkitt's lymphoma cells, and determine site-specific glycosylation changes that occurred upon inhibition of fucosylation at high confidence.
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Project description:Disease-associated aberrant glycosylation may be protein specific and glycosylation site specific. Quantitative assessment of glycosylation changes at a site-specific molecular level may represent one of the initial steps for systematically revealing the glycosylation abnormalities associated with a disease or biological state. Comparative quantitative profiling of glycoproteome to provide accurate quantification of site-specific glycosylation occupancy has been a challenging task, requiring a concerted approach drawing from a variety of techniques. In this report, we present a quantitative glycoproteomics method that allows global scale identification and comparative quantification of glycosylation site occupancy using mass spectrometry. We further demonstrated this approach by quantitatively characterizing the N-glycoproteome of human pancreas.
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Project description:Mass spectrometry (MS) can unlock crucial insights into the intricate world of glycosylation analysis. Despite its immense potential, the qualitative and quantitative analysis of isobaric glycopeptide structures remains one of the most daunting hurdles in the field of glycoproteomics. The ability to distinguish between these complex glycan structures poses a significant challenge, hindering our ability to accurately measure and understand the role of glycoproteins in biological systems. A few recent publications described the use of collision energy (CE) modulation to improve structural elucidation, especially for qualitative purposes. Different linkages of glycan units usually demonstrate different stabilities under CID/HCD fragmentation conditions. Fragmentation of the glycan moiety produces low molecular weight ions (oxonium ions) that can serve as a structure-specific signature for specific glycan moieties, however, specificity of these fragments has never been examined closely. Here, we investigated fragmentation specificity using synthetic stable isotope-labelled glycopeptide standards. These standards were isotopically labelled at the reducing terminal GlcNAc, which allowed us to resolve fragments produced by oligomannose core moiety and fragments generated from outer antennary structures. Our research identified the potential for false positive structure assignments due to the occurrence of "Ghost" fragments resulting from single glyco unit rearrangement or mannose core fragmentation within the collision cell. To mitigate this issue, we have established a minimal intensity threshold for these fragments to prevent the misidentification of structure-specific fragments in glycoproteomics analysis. Our findings provide a crucial step forward in the quest for more accurate and reliable glycoproteomics measurements.Graphical abstract
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Project description:Mass spectrometry (MS) can unlock crucial insights into the intricate world of glycosylation analysis. Despite its immense potential, the qualitative and quantitative analysis of isobaric glycopeptide structures remains one of the most daunting hurdles in the field of glycoproteomics. The ability to distinguish between these complex glycan structures poses a significant challenge, hindering our ability to accurately measure and understand the role of glycoproteins in biological systems. A few recent publications described the use of collision energy (CE) modulation to improve structural elucidation, especially for qualitative purposes. Different linkages of glycan units usually demonstrate different stabilities under CID/HCD fragmentation conditions. Fragmentation of the glycan moiety produces low molecular weight ions (oxonium ions) that can serve as a structure-specific signature for specific glycan moieties; however, the specificity of these fragments has never been examined closely. Here, we particularly focused on N-glycoproteomics analysis and investigated fragmentation specificity using synthetic stable isotope-labeled N-glycopeptide standards. These standards were isotopically labeled at the reducing terminal GlcNAc, which allowed us to resolve fragments produced by the oligomannose core moiety and fragments generated from outer antennary structures. Our research identified the potential for false-positive structure assignments due to the occurrence of "Ghost" fragments resulting from single glyco unit rearrangement or mannose core fragmentation within the collision cell. To mitigate this issue, we have established a minimal intensity threshold for these fragments to prevent misidentification of structure-specific fragments in glycoproteomics analysis. Our findings provide a crucial step forward in the quest for more accurate and reliable glycoproteomics measurements.
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Project description:High-Fidelity, Large-Scale Targeted Profiling of Microsatellites
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Project description:High-Fidelity, Large-Scale Targeted Profiling of Microsatellites
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Project description:The protein quality control sensors UDP-glucose: glycoprotein glucosyltransferase (UGGT) 1 and 2 are proposed to act as gatekeepers of the early secretory pathway. They initiate rebinding to the carbohydrate-dependent chaperones calnexin and calreticulin that associate with proteins possessing monoglucosylated glycans. The UGGTs control glycoprotein exit from the endoplasmic reticulum (ER) for trafficking to the Golgi or ER retention to provide additional folding opportunities. A quantitative glycoproteomics strategy was used to identify cellular glycoproteins modified by the UGGTs at endogenous levels and delineate the specificities of UGGT1 and UGGT2. UGGT substrates were comprised of seventy-one mainly large multidomain and heavily glycosylated proteins when compared to the general N-glycome. UGGT1 was the dominant glucosyltransferase with a preference towards large plasma membrane proteins whereas UGGT2 favored the modification of smaller, soluble lysosomal proteins. This study provides insight into the cellular secretory load that utilizes multiple rounds of carbohydrate-dependent chaperone intervention for proper maturation.
2020-11-28 | GSE162262 | GEO
Project description:Although the composition of donkey milk is similar to that of human milk, systematic comparisons of the site-specific N-glycosylation patterns of their whey proteins are lacking. In this study, hydrophilic interaction chromatography-based enrichment of intact N-glycopeptides, coupled with a site-specific glycoproteomics strategy, was used to systematically characterise whey N-glycoproteins in donkey colostrum (DC), donkey mature milk (DM), human colostrum (HC), and human mature milk (HM) for the first time. We identified 628, 347, 868, and 425 site-specific N-glycans mapped to 135, 67, 113, and 60 glycoproteins in DC, DM, HC, and HM, respectively. Bioinformatic analysis revealed the potential biological effects of N-glycosylation modifications on the whey proteins themselves. Our findings elucidated the composition of donkey and human milk whey N-glycoproteins and their potential structure-activity relationships and provided guidance for the production of specific functional donkey milk products and the development of donkey milk-based infant formulas.
2024-03-19 | PXD050759 |
Project description:Protein glycosylation is a highly important, yet a poorly understood protein post-translational modification. Thousands of possible glycan structures and compositions create potential for tremendous site heterogeneity and analytical challenge. A lack of suitable analytical methods for large-scale analyses of intact glycopeptides has ultimately limited our abilities to both address the degree of heterogeneity across the glycoproteome and to understand how it contributes biologically to complex systems. Here we show that N-glycoproteome site-specific microheterogeneity can be captured at a global level via glycopeptide profiling with activated ion electron transfer dissociation (AI-ETD), enabling characterization of nearly 2,100 N-glycosites (> 7,500 unique N-glycopeptides) from mouse brain tissue. Moreover, we have used this unprecedented scale of glycoproteomic data to develop several new visualizations that will prove useful for analyzing intact glycopeptides in future studies. Our data reveal that N-glycosylation profiles can differ between subcellular regions and structural domains and that N-glycosite heterogeneity manifests in several different forms, including dramatic differences in glycosites on the same protein.
2019-04-02 | PXD011533 | Pride
Project description:IntroductionThe human plasma glycoproteome holds enormous potential to identify personalized biomarkers for diagnostics. Glycoproteomics has matured into a technology for plasma N-glycoproteome analysis but further evolution towards clinical applications depends on the clinical validity and understanding of protein- and site-specific glycosylation changes in disease.ObjectivesHere, we exploited the uniqueness of a patient cohort of genetic defects in well-defined glycosylation pathways to assess the clinical applicability of plasma N-glycoproteomics.MethodsComparative glycoproteomics was performed of blood plasma from 40 controls and 74 patients with 13 different genetic diseases that impact the protein N-glycosylation pathway. Baseline glycosylation in healthy individuals was compared to reference glycome and intact transferrin protein mass spectrometry data. Use of glycoproteomics data for biomarker discovery and sample stratification was evaluated by multivariate chemometrics and supervised machine learning. Clinical relevance of site-specific glycosylation changes were evaluated in the context of genetic defects that lead to distinct accumulation or loss of specific glycans. Integrated analysis of site-specific glycoproteome changes in disease was performed using chord diagrams and correlated with intact transferrin protein mass spectrometry data.ResultsGlycoproteomics identified 191 unique glycoforms from 58 unique peptide sequences of 34 plasma glycoproteins that span over 3 magnitudes of abundance in plasma. Chemometrics identified high-specificity biomarker signatures for each of the individual genetic defects with better stratification performance than the current diagnostic standard method. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and protein-intrinsic factors.ConclusionOur work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the glycobiological mechanisms underlying human disease.
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