Dataset Information

Characterization of sialylated N- and O-glycopeptides from complex proteomes on an Orbitrap Fusion Tribrid mass spectrometer by Isotope Targeted Glycoproteomics (IsoTaG). Application to azido and alkynyl sugars

ABSTRACT: Protein glycosylation is a post-translational modification (PTM) responsible for many aspects of proteomic diversity and biological regulation. Correlation of the intact glycoform to the protein attachment site is a critical step to assign functional roles to specific glycoproteins. Isotope targeted glycoproteomics (IsoTaG) is a mass-independent mass spectrometry method to characterize intact, metabolically labeled glycopeptides from complex proteomes. IsoTaG was applied to conditioned media from PC-3 cells labeled with alkynyl or azido sugars to reveal the sialylated glycoproteome. Analysis on an Orbitrap Fusion Tribrid mass spectrometer resulted in characterization of 699 intact glycopeptides from 192 glycoproteins. These intact glycopeptides represent a total of eight sialylated glycoforms across 126 Nand 576 O-glycopeptides. IsoTaG is an effective platform for identification of intact glycopeptides labeled by alkynyl or azido-glycans and will facilitate further studies on the role of the glycoproteome in biology.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Cell Culture

DISEASE(S): Prostate Adenocarcinoma

SUBMITTER: Christina Woo

LAB HEAD: Christina Woo

PROVIDER: PXD004302 | Pride | 2017-02-22

REPOSITORIES: Pride

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Isotope-targeted glycoproteomics (IsoTaG) analysis of sialylated N- and O-glycopeptides on an Orbitrap Fusion Tribrid using azido and alkynyl sugars.

Woo Christina M CM Felix Alejandra A Zhang Lichao L Elias Joshua E JE Bertozzi Carolyn R CR

Analytical and bioanalytical chemistry 20160930 2

Protein glycosylation is a post-translational modification (PTM) responsible for many aspects of proteomic diversity and biological regulation. Assignment of intact glycan structures to specific protein attachment sites is a critical step towards elucidating the function encoded in the glycome. Previously, we developed isotope-targeted glycoproteomics (IsoTaG) as a mass-independent mass spectrometry method to characterize azide-labeled intact glycopeptides from complex proteomes. Here, we extend ...[more]

PMID: 27695962

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Project description:Protein O-glycosylation has long been recognized to be closely associated with many diseases, particularly with tumor proliferation, invasion and metastasis. The ability to efﬁciently proﬁle the variation of O-glycosylation in large-scale clinical samples provides an important approach for the development of biomarkers for cancer diagnosis and for therapeutic response evaluation. Therefore, mass spectrometry (MS)-based techniques for high throughput, in-depth and reliable elucidation of protein O-glycosylation in large clinical cohorts are in high demand. However, the wide existence of serine and threonine residues in the proteome and the tens of mammalian O-glycan types lead to extremely large searching space composed of millions of theoretical combinations of peptides and O-glycans for intact O-glycopeptide database searching. As a result, exceptionally long time is required for database searching which is a major obstacle in O-glycoproteome studies of large clinical cohorts. More importantly, due to the low abundance and poor ionization of intact O-glycopeptides and the stochastic nature of data-dependent MS2 acquisition, substantially elevated missing data levels are inevitable as the sample number increases, which undermines the quantitative comparison across samples. Therefore, we report a new MS data processing strategy that integrates glycoform-specific database searching, reference library-based MS1 feature matching and MS2 identification propagation for fast identification, in-depth and reproducible label-free quantification of O-glycosylation of human urinary proteins. This strategy increases the database searching speeds by up to 20-fold and leads to a 30-40% enhanced intact O-glycopeptide quantification in individual samples with an obviously improved reproducibility. In total, we obtained quantitative information for 1068 intact O-glycopeptides across 36 healthy human urine samples with a 30-40% reduction in the amount of missing data. This is currently the largest dataset of urinary O-glycoproteome and demonstrates the application potential of this new strategy in large-scale clinical investigations.

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