Systematic Evaluation of Affinity Enrichment Methods for O-GlcNAc Proteomics.

O-Linked ß-N-acetylglucosamine (O-GlcNAc) modification (i.e., O-GlcNAcylation) on proteins plays critical roles in the regulation of diverse biological processes. However, protein O-GlcNAcylation analysis, especially at a large scale, has been a challenge. So far, a number of enrichment materials and methods have been developed for site-specific O-GlcNAc proteomics in different biological settings. Despite the presence of multiple methods, their performance for the O-GlcNAc proteomics is largely unclear. In this work, by using the lysates of PANC-1 cells (a pancreatic cancer cell line), we provided a head-to-head comparison of three affinity enrichment methods and materials (i.e., antibody, lectin AANL6, and an OGA mutant) for site-specific O-GlcNAc proteomics. The enriched peptides were analyzed by HCD product-dependent EThcD (i.e., HCD-pd-EThcD) mass spectrometry. The resulting data files were processed by three different data analysis packages (i.e., Sequest HT, Byonic, and FragPipe). Our data suggest that each method captures a subpopulation of the O-GlcNAc proteins. Besides the enrichment methods, we also observe complementarity between the different data analysis tools. Thus, combining different approaches holds promise for enhanced coverage of O-GlcNAc proteomics.

An integrated strategy for the construction of a species-specific glycan library for mass spectrometry-based intact glycopeptide analyses.

Mass spectrometry (MS)-based strategies and related software tools using glycan mass lists have greatly facilitated the analysis of intact glycopeptides. Most glycan mass lists are derived from normal glycans of mammals and contain limited monosaccharides, which has significantly hindered high throughput studies of unusual glycosylation events observed in other species. In this work, an integrated strategy was developed for the construction of a species-specific glycan mass list from glycan structure databases and published papers. We developed a computational tool called LibGlycan, which could process the different formats of glycans. Then, the software tool generated a glycan library that contained the monoisotope mass, average mass, isotope distribution, and glycan mass list for input into Byonic software. This strategy was applied to analyze the N-glycosylation of rice roots and O-glycosylation of Acinetobacter baumannii ATCC17978, leading to the identification of 296 and 145 intact glycopeptides respectively. Combined, these results show that this strategy is a robust computational approach for the determination of glycan diversity within different complex biological systems.

Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics.

Glycopeptides in peptide or digested protein samples pose a number of analytical and bioinformatics challenges beyond those posed by unmodified peptides or peptides with smaller posttranslational modifications. Exact structural elucidation of glycans is generally beyond the capability of a single mass spectrometry experiment, so a reasonable level of identification for tandem mass spectrometry, taken by several glycopeptide software tools, is that of peptide sequence and glycan composition, meaning the number of monosaccharides of each distinct mass, e.g., HexNAc(2)Hex(5) rather than man5. Even at this level, however, glycopeptide analysis poses challenges: finding glycopeptide spectra when they are a tiny fraction of the total spectra; assigning spectra with unanticipated glycans, not in the initial glycan database; and finding, scoring, and labeling diagnostic peaks in tandem mass spectra. Here, we discuss recent improvements to Byonic, a glycoproteomics search program, that address these three issues. Byonic now supports filtering spectra by m/z peaks, so that the user can limit attention to spectra with diagnostic peaks, e.g., at least two out of three of 204.087 for HexNAc, 274.092 for NeuAc (with water loss), and 366.139 for HexNAc-Hex, all within a set mass tolerance, e.g., ± 0.01 Da. Also, new is glycan "wildcard" search, which allows an unspecified mass within a user-set mass range to be applied to N- or O-linked glycans and enables assignment of spectra with unanticipated glycans. Finally, the next release of Byonic supports user-specified peak annotations from user-defined posttranslational modifications. We demonstrate the utility of these new software features by finding previously unrecognized glycopeptides in publicly available data, including glycosylated neuropeptides from rat brain.

Differential Quantitative Determination of Site-Specific Intact N-Glycopeptides in Serum Haptoglobin between Hepatocellular Carcinoma and Cirrhosis Using LC-EThcD-MS/MS.

Intact N-glycopeptide analysis remains challenging due to the complexity of glycopeptide structures, low abundance of glycopeptides in protein digests, and difficulties in data interpretation/quantitation. Herein, we developed a workflow that involved advanced methodologies, the EThcD-MS/MS fragmentation method and data interpretation software, for differential analysis of the microheterogeneity of site-specific intact N-glycopeptides of serum haptoglobin between early hepatocellular carcinoma (HCC) and liver cirrhosis. Haptoglobin was immunopurified from 20 µL of serum in patients with early HCC, liver cirrhosis, and healthy controls, respectively, followed by trypsin/GluC digestion, glycopeptide enrichment, and LC-EThcD-MS/MS analysis. Identification and differential quantitation of site-specific N-glycopeptides were performed using a combination of Byonic and Byologic software. In total, 93, 87, and 68 site-specific N-glycopeptides were identified in early HCC, liver cirrhosis, and healthy controls, respectively, with high confidence. The increased variety of N-glycopeptides in liver diseases compared to healthy controls was due to increased branching with hyper-fucosylation and sialylation. Differential quantitation analysis showed that 5 site-specific N-glycopeptides on sites N184 and N241 were significantly elevated in early HCC compared to cirrhosis ( p < 0.05) and normal controls ( p ≤ 0.001). The result demonstrates that the workflow provides a strategy for detailed profiles of N-glycopeptides of patient samples as well as for relative quantitation to determine the level changes in site-specific N-glycopeptides between disease states.

Extending Proteome Coverage by Combining MS/MS Methods and a Modified Bioinformatics Platform Adapted for Database Searching of Positive and Negative Polarity 193 nm Ultraviolet Photodissociation Mass Spectra.

To extend proteome coverage obtained from bottom-up mass spectrometry approaches, three complementary ion activation methods, higher energy collision dissociation (HCD), ultraviolet photodissociation (UVPD), and negative mode UVPD (NUVPD), are used to interrogate the tryptic peptides in a human hepatocyte lysate using a high performance Orbitrap mass spectrometer. The utility of combining results from multiple activation techniques (HCD+UVPD+NUVPD) is analyzed for total depth and breadth of proteome coverage. This study also benchmarks a new version of the Byonic algorithm, which has been customized for database searches of UVPD and NUVPD data. Searches utilizing the customized algorithm resulted in over 50% more peptide identifications for UVPD and NUVPD tryptic peptide data sets compared to other search algorithms. Inclusion of UVPD and NUVPD spectra resulted in over 600 additional protein identifications relative to HCD alone.

Sequential fragment ion filtering and endoglycosidase-assisted identification of intact glycopeptides.

Detailed characterization of glycoprotein structures requires determining both the sites of glycosylation as well as the glycan structures associated with each site. In this work, we developed an analytical strategy for characterization of intact N-glycopeptides in complex proteome samples. In the first step, tryptic glycopeptides were enriched using ZIC-HILIC. Secondly, a portion of the glycopeptides was treated with endoglycosidase H (Endo H) to remove high-mannose (Man) and hybrid N-linked glycans. Thirdly, a fraction of the Endo H-treated glycopeptides was further subjected to PNGase F treatment in 18O water to remove the remaining complex glycans. The intact glycopeptides and deglycosylated peptides were analyzed by nano-RPLC-MS/MS, and the glycan structures and the peptide sequences were identified by using the Byonic or pFind tools. Sequential digestion by endoglycosidase provided candidate glycosites information and indication of the glycoforms on each glycopeptide, thus helping to confine the database search space and improve the confidence regarding intact glycopeptide identification. We demonstrated the effectiveness of this approach using RNase B and IgG and applied this sequential digestion strategy for the identification of glycopeptides from the HepG2 cell line. We identified 4514 intact glycopeptides coming from 947 glycosites and 1011 unique peptide sequences from HepG2 cells. The intensity of different glycoforms at a specific glycosite was obtained to reach the occupancy ratios of site-specific glycoforms. These results indicate that our method can be used for characterizing site-specific protein glycosylation in complex samples. Graphical abstract Through integrating the information of intact glycopeptide, fragment ions filters and endoglycosidase digestion, the reliability of the identification could be significantly improved. We quantified the site-specific glycoforms occupancy ratios through the MS response signaling of each glycopeptide at the same time.

Detection and Measurement of Methionine Oxidation in Proteins.

Methionine oxidation is a prevalent modification found in proteins both in biological settings and in the manufacturing of biotherapeutic molecules. In cells, the oxidation of specific methionine sites can modulate protein function or promote interactions that trigger signaling pathways. In biotherapeutic development, the formation of oxidative species could be detrimental to the efficacy or safety of the drug product. Thus, methionine oxidation is a critical quality attribute that needs to be monitored throughout development. Here we describe a method using LC/MS/MS to identify site-specific methionine modifications in proteins. Antibodies are stressed with hydrogen peroxide, and the level of Met oxidation is compared to that of reference molecules. The protocols presented here are not specific to methionine and can be used more generally to identify other PTM risk sites in molecules after various types of treatments. © 2017 by John Wiley & Sons, Inc.

Automated Antibody De Novo Sequencing and Its Utility in Biopharmaceutical Discovery.

Applications of antibody de novo sequencing in the biopharmaceutical industry range from the discovery of new antibody drug candidates to identifying reagents for research and determining the primary structure of innovator products for biosimilar development. When murine, phage display, or patient-derived monoclonal antibodies against a target of interest are available, but the cDNA or the original cell line is not, de novo protein sequencing is required to humanize and recombinantly express these antibodies, followed by in vitro and in vivo testing for functional validation. Availability of fully automated software tools for monoclonal antibody de novo sequencing enables efficient and routine analysis. Here, we present a novel method to automatically de novo sequence antibodies using mass spectrometry and the Supernovo software. The robustness of the algorithm is demonstrated through a series of stress tests. Graphical Abstract ᅟ.

Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. SIGNIFICANCE: We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans.

Toward Automated N-Glycopeptide Identification in Glycoproteomics.

Advances in software-driven glycopeptide identification have facilitated N-glycoproteomics studies reporting thousands of intact N-glycopeptides, i.e., N-glycan-conjugated peptides, but the automated identification process remains to be scrutinized. Herein, we compare the site-specific glycoprofiling efficiency of the PTM-centric search engine Byonic relative to manual expert annotation utilizing typical glycoproteomics acquisition and data analysis strategies but with a single glycoprotein, the uncharacterized multiple N-glycosylated human basigin. Detailed site-specific reference glycoprofiles of purified basigin were manually established using ion-trap CID-MS/MS and high-resolution Q-Exactive Orbitrap HCD-MS/MS of tryptic N-glycopeptides and released N-glycans. The micro- and macroheterogeneous basigin N-glycosylation was site-specifically glycoprofiled using Byonic with or without a background of complex peptides using Q-Exactive Orbitrap HCD-MS/MS. The automated glycoprofiling efficiencies were assessed against the site-specific reference glycoprofiles and target/decoy proteome databases. Within the limits of this single glycoprotein analysis, the search criteria and confidence thresholds (Byonic scores) recommended by the vendor provided high glycoprofiling accuracy and coverage (both >80%) and low peptide FDRs (<1%). The data complexity, search parameters including search space (proteome/glycome size), mass tolerance and peptide modifications, and confidence thresholds affected the automated glycoprofiling efficiency and analysis time. Correct identification of ambiguous peptide modifications (methionine oxidation/carbamidomethylation) whose mass differences coincide with several monosaccharide mass differences (Fuc/Hex/HexNAc) and of ambiguous isobaric (Hex1NeuAc1-R/Fuc1NeuGc1-R) or near-isobaric (NeuAc1-R/Fuc2-R) monosaccharide subcompositions remains challenging in automated glycoprofiling, arguing particular attention paid to N-glycopeptides displaying such "difficult-to-identify" features. This study provides valuable insights into the automated glycopeptide identification process, stimulating further developments in FDR-based glycoproteomics.