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Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identification using N-glycoproteomics data; however, symmetric "mirror" branch isomers and linkage isomers are largely unresolved. Here, we report deep structure-level N-glycan identification using feature-induced structure diagnosis (FISD) integrated with a deep learning model. A neural network model is integrated to conduct the identification of featured N-glycan motifs and boosts the process of structure diagnosis and distinction for linkage isomers. By adopting publicly available N-glycoproteomics datasets of five mouse tissues (17,136 intact N-glycopeptide spectrum matches) and a consideration of 23 motif features, a deep learning model integrated with a convolutional autoencoder and a multilayer perceptron was trained to be capable of predicting N-glycan featured motifs in the MS/MS spectra with previously identified compositions. In the test of the trained model, a prediction accuracy of 0.8 and AUC value of 0.95 were achieved; 5701 previously unresolved N-glycan structures were assigned by matched structure-diagnostic ions; and by using an explainable learning algorithm, two new fragmentation features of m/z = 674.25 and m/z = 835.28 were found to be significant to three N-glycan structure motifs with fucose, NeuAc, and NeuGc, proving the capability of FISD to discover new features in the MS/MS spectra.

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N-linked glycosylation (N-glycosylation) is a common protein post-translational modification, occurring on more than half of mammalian proteins; in striking contract with small molecule modifications (such as methylation, phosphorylation) with only single structures, N-glycosylation has multiple dimensional structural features (monosaccharide composition, sequence, linkage, anomer), which generates enormous N-glycan structures; and these structures widely regulate protein structure and functions. For the modification site, N-glycosylation occurs on the Asn residue among the consensus N-X-S/T/C (X≠P) motif; mutation-originated amino acid change may lead to loss of such an original motif and thus loss-of-glycosylation (LoG) or gain of such a new motif and thus gain-of-glycosylation (GoG). Both LoG and GoG generates new structures and functions of glycoproteins, which has been observed in the S protein of SARS-Cov-2 as well as malignant diseases. Here we report our glycoproteome-wide qualitative N-glycoproteomics characterization of GoGs in breast cancer Adriamycin drug resistance (ADR) cells (MCF-7/ADR) and cancer stem cells (MCF-7/ADR CSCs); comprehensive N-glycosite and N-glycan structure information at the intact N-glycopeptide level were reported.

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Proteomics studies the proteome of organisms, especially proteins that are differentially expressed under certain physiological or pathological conditions; qualitative identification of protein sequences and posttranslational modifications (PTMs) and their positions can help us systematically understand the structure and function of proteoforms. With the development and relative popularity of soft ionization technology (such as electrospray ionization technology) and high mass measurement accuracy and high-resolution mass spectrometers (such as orbitrap), the mass spectrometry (MS) characterization of complete proteins (the so-called top-down proteomics) has become possible and has gradually become popular. Corresponding database search engines and protein identification bioinformatics tools have also been greatly developed. This chapter provides a brief overview of intact protein database search algorithm "isotopic mass-to-charge ratio and envelope fingerprinting" and search engine ProteinGoggle.

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The N-glycosylation is an important bioprocess in plant. Monosaccharide composition-level characterization at the intact N-glycopeptides has been extensively reported, yet structure-specific study to resolve multiple sequence structures of a single composition is still lacking. Here, we present a comprehensive structure-specific identification of intact N-glycopeptides of Arabidopsis with both HILIC and RAX enrichment, as well as GPSeeker and pGlyco database search. With target-decoy searches and spectrum-level FDR ≤ 1%, 5,687 N-glycopeptides from 3,713 N-glycosites of 3,140 N-glycoproteins were identified, which represents the currently most comprohensive profilling to our best knowledge. Wtih the experimental evidence support of structure-diagnostic fragment ions, 81 glycan structures from 54 glcan compostions were unambiguouly distinguished. The comprehensive experimental site- and structure-specific N-glycosylation data reported in this study will serve as a fundamental valuable reference for the coming functional studies of this widely adopted model organism of plant.

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Coronavirus disease 2019 (COVID-19), a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 235 million individuals and led to more than 4.8 million deaths worldwide as of October 5 2021. Cryo-electron microscopy and topology show that the SARS-CoV-2 genome encodes lots of highly glycosylated proteins, such as spike (S), envelope (E), membrane (M), and ORF3a proteins, which are responsible for host recognition, penetration, binding, recycling and pathogenesis. Here we reviewed the detections, substrates, biological functions of the glycosylation in SARS-CoV-2 proteins as well as the human receptor ACE2, and also summarized the approved and undergoing SARS-CoV-2 therapeutics associated with glycosylation. This review may not only broad the understanding of viral glycobiology, but also provide key clues for the development of new preventive and therapeutic methodologies against SARS-CoV-2 and its variants.

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