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Protein glycosylation is a highly important, yet poorly understood protein post-translational modification. Thousands of possible glycan structures and compositions create potential for tremendous site heterogeneity. A lack of suitable analytical methods for large-scale analyses of intact glycopeptides has limited our abilities both to address the degree of heterogeneity across the glycoproteome and to understand how this contributes biologically to complex systems. Here we show that N-glycoproteome site-specific microheterogeneity can be captured via large-scale glycopeptide profiling methods enabled by activated ion electron transfer dissociation (AI-ETD), ultimately characterizing 1,545 N-glycosites (>5,600 unique N-glycopeptides) from mouse brain tissue. 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. Moreover, we use this large-scale glycoproteomic dataset to develop several visualizations that will prove useful for analyzing intact glycopeptides in future studies. Mass spectrometry facilitates large-scale glycosylation profiling but in-depth analysis of intact glycopeptides is still challenging. Here, the authors show that activated ion electron transfer dissociation is suitable for glycopeptide fragmentation and improves glycoproteome coverage.

Protein glycosylation analysis is challenging due to the structural variety of complex conjugates. However, chromatographically separating glycans attached to tryptic peptides enables their site-specific characterization. For this purpose, we have shown the importance of selecting a suitable hydrophilic interaction liquid chromatography (HILIC) stationary phase in the separation of glycopeptides and their isomers. Three different HILIC stationary phases, i.e., HALO® penta-HILIC, Glycan ethylene bridged hybrid (BEH) Amide, and ZIC-HILIC, were compared in the separation of complex N-glycopeptides of hemopexin and Immunoglobulin G glycoproteins. The retention time increased with the polarity of the glycans attached to the same peptide backbone in all HILIC columns tested in this study, except for the ZIC-HILIC column when adding sialic acid to the glycan moiety, which caused electrostatic repulsion with the negatively charged sulfobetaine functional group, thereby decreasing retention. The HALO® penta-HILIC column provided the best separation results, and the ZIC-HILIC column the worst. Moreover, we showed the potential of these HILIC columns for the isomeric separation of fucosylated and sialylated glycoforms. Therefore, HILIC is a useful tool for the comprehensive characterization of glycoproteins and their isomers.

Selecting for microorganisms resistant to known antibiotics enables discovery of strains that produce structurally related compounds. Microbially derived natural products are major sources of antibiotics and other medicines, but discovering new antibiotic scaffolds and increasing the chemical diversity of existing ones are formidable challenges. We have designed a screen to exploit the self-protection mechanism of antibiotic producers to enrich microbial libraries for producers of selected antibiotic scaffolds. Using resistance as a discriminating criterion we increased the discovery rate of producers of both glycopeptide and ansamycin antibacterial compounds by several orders of magnitude in comparison with historical hit rates. Applying a phylogeny-based screening filter for biosynthetic genes enabled the binning of producers of distinct scaffolds and resulted in the discovery of a glycopeptide antibacterial compound, pekiskomycin, with an unusual peptide scaffold. This strategy provides a means to readily sample the chemical diversity available in microbes and offers an efficient strategy for rapid discovery of microbial natural products and their associated biosynthetic enzymes.

Glycopeptide enrichment is a crucial step in glycoproteomics for which hydrophilic interaction chromatography (HILIC) has extensively been applied due to its low bias towards different glycan types. A systematic evaluation of applicable HILIC mobile phases on glycopeptide enrichment efficiency and selectivity is, to date, however, still lacking. Here, we present a novel, simplified technique for HILIC enrichment termed “Drop-HILIC”, which was applied to systematically evaluate the mobile phase effect on ZIC-HILIC (zwitterionic type of hydrophilic interaction chromatography) glycopeptide enrichment. The four most commonly used MS compatible organic solvents were investigated: (i) acetonitrile, (ii) methanol, (iii) ethanol and (iv) isopropanol. Glycopeptide enrichment efficiencies were evaluated for each solvent system using samples of increasing complexity ranging from well-defined synthetic glycopeptides spiked into different concentrations of tryptic BSA peptides, followed by standard glycoproteins, and a complex sample derived from human (depleted and non-depleted) serum. ZIC-HILIC glycopeptide efficiency largely relied upon the used solvent. Different organic mobile phases enriched distinct glycopeptide subsets in a peptide backbone hydrophilicity-dependant manner. Acetonitrile provided the best compromise for the retention of both hydrophilic and hydrophobic glycopeptides, whereas methanol was confirmed to be unsuitable for this purpose. The enrichment efficiency of ethanol and isopropanol towards highly hydrophobic glycopeptides was compromised as considerable co-enrichment of unmodified peptides occurred, though for some hydrophobic glycopeptides isopropanol showed the best enrichment properties. This study shows that even minor differences in the peptide backbone and solvent do significantly influence HILIC glycopeptide enrichment and need to be carefully considered when employed for glycopeptide enrichment. Graphical Abstract The organic solvent plays a crucial role in ZIC-HILIC glycopeptide enrichment

The majority of therapies that target individual proteins rely on specific activity-modulating interactions with the target protein—for example, enzyme inhibition or ligand blocking. However, several major classes of therapeutically relevant proteins have unknown or inaccessible activity profiles and so cannot be targeted by such strategies. Protein-degradation platforms such as proteolysis-targeting chimaeras (PROTACs) 1 , 2 and others (for example, dTAGs 3 , Trim-Away 4 , chaperone-mediated autophagy targeting 5 and SNIPERs 6 ) have been developed for proteins that are typically difficult to target; however, these methods involve the manipulation of intracellular protein degradation machinery and are therefore fundamentally limited to proteins that contain cytosolic domains to which ligands can bind and recruit the requisite cellular components. Extracellular and membrane-associated proteins—the products of 40% of all protein-encoding genes 7 —are key agents in cancer, ageing-related diseases and autoimmune disorders 8 , and so a general strategy to selectively degrade these proteins has the potential to improve human health. Here we establish the targeted degradation of extracellular and membrane-associated proteins using conjugates that bind both a cell-surface lysosome-shuttling receptor and the extracellular domain of a target protein. These initial lysosome-targeting chimaeras, which we term LYTACs, consist of a small molecule or antibody fused to chemically synthesized glycopeptide ligands that are agonists of the cation-independent mannose-6-phosphate receptor (CI-M6PR). We use LYTACs to develop a CRISPR interference screen that reveals the biochemical pathway for CI-M6PR-mediated cargo internalization in cell lines, and uncover the exocyst complex as a previously unidentified—but essential—component of this pathway. We demonstrate the scope of this platform through the degradation of therapeutically relevant proteins, including apolipoprotein E4, epidermal growth factor receptor, CD71 and programmed death-ligand 1. Our results establish a modular strategy for directing secreted and membrane proteins for lysosomal degradation, with broad implications for biochemical research and for therapeutics. Lysosome-targeting chimaeras—in which a small molecule or antibody is connected to a glycopeptide ligand to form a conjugate that can bind a cell-surface lysosome-shuttling receptor and a protein target—are used to achieve the targeted degradation of extracellular and membrane proteins.

Recent advances in methods for enrichment and mass spectrometric analysis of intact glycopeptides have produced large-scale glycoproteomics datasets, but interpreting these data remains challenging. We present MSFragger-Glyco, a glycoproteomics mode of the MSFragger search engine, for fast and sensitive identification of N - and O -linked glycopeptides and open glycan searches. Reanalysis of recent N -glycoproteomics data resulted in annotation of 80% more glycopeptide spectrum matches (glycoPSMs) than previously reported. In published O -glycoproteomics data, our method more than doubled the number of glycoPSMs annotated when searching the same glycans as the original search, and yielded 4- to 6-fold increases when expanding searches to include additional glycan compositions and other modifications. Expanded searches also revealed many sulfated and complex glycans that remained hidden to the original search. With greatly improved spectral annotation, coupled with the speed of index-based scoring, MSFragger-Glyco makes it possible to comprehensively interrogate glycoproteomics data and illuminate the many roles of glycosylation. MSFragger-Glyco allows identification of N - and O -linked glycopeptides using the localization-aware open search strategy of the MSFragger search engine.

A novel quantitative approach to identify intact glycopeptides from comparative proteomic data sets, allowing inference of complex glycan structures and direct mapping of them to sites within the associated proteins at the proteome scale. Pinpointing glycoproteins The activity of more than half of human proteins is modified by their attachment to carbohydrate structures. To improve the identification and functional validation of such protein glycosylation, Josef Penninger and colleagues have developed a proteomics-based approach to identifying intact glycopeptides. The technique has high specificity and can pinpoint the location within the proteins where the glycosyl group has attached. The authors used their approach on human and mouse embryonic stem cells and identified nearly twice as many glycoproteins than were previously known. This analysis additionally led to the identification of several glycosylated 'stemness' factors, as well as of evolutionarily conserved and species-specific glycoproteins. The team also used the method to provide molecular insights into the toxicity of the bioweapon ricin. Glycosylation, the covalent attachment of carbohydrate structures onto proteins, is the most abundant post-translational modification 1 . Over 50% of human proteins are glycosylated, which alters their activities in diverse fundamental biological processes 2 , 3 . Despite the importance of glycosylation in biology 4 , the identification and functional validation of complex glycoproteins has remained largely unexplored. Here we develop a novel quantitative approach to identify intact glycopeptides from comparative proteomic data sets, allowing us not only to infer complex glycan structures but also to directly map them to sites within the associated proteins at the proteome scale. We apply this method to human and mouse embryonic stem cells to illuminate the stem cell glycoproteome. This analysis nearly doubles the number of experimentally confirmed glycoproteins, identifies previously unknown glycosylation sites and multiple glycosylated stemness factors, and uncovers evolutionarily conserved as well as species-specific glycoproteins in embryonic stem cells. The specificity of our method is confirmed using sister stem cells carrying repairable mutations in enzymes required for fucosylation, Fut9 and Slc35c1. Ablation of fucosylation confers resistance to the bioweapon ricin 5 , 6 , and we discover proteins that carry a fucosylation-dependent sugar code for ricin toxicity. Mutations disrupting a subset of these proteins render cells ricin resistant, revealing new players that orchestrate ricin toxicity. Our comparative glycoproteomics platform, SugarQb, enables genome-wide insights into protein glycosylation and glycan modifications in complex biological systems.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometry based glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved ‘high-coverage’ and ‘high-accuracy’ glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.This analysis presents the results of a community-based evaluation of existing software for large-scale glycopeptide data analysis.

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with 15 N/ 13 C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues. Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus . O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. It also introduces a classification scheme to unify data reporting for glycoproteomics.