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Protein glycosylation is a widespread posttranslational modification that can impact the function of proteins. Dysregulated protein glycosylation has been linked to several diseases, including chronic respiratory diseases (CRDs). CRDs pose a significant public health threat globally, affecting the airways and other lung structures. Emerging researches suggest that glycosylation plays a significant role in regulating inflammation associated with CRDs. This review offers an overview of the abnormal glycoenzyme activity and corresponding glycosylation changes involved in various CRDs, including chronic obstructive pulmonary disease, asthma, cystic fibrosis, idiopathic pulmonary fibrosis, pulmonary arterial hypertension, non-cystic fibrosis bronchiectasis, and lung cancer. Additionally, this review summarizes recent advances in glycomics and glycoproteomics-based protein glycosylation analysis of CRDs. The potential of glycoenzymes and glycoproteins for clinical use in the diagnosis and treatment of CRDs is also discussed.

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5–40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

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 spectrometrybased 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.

Purpose. To assess the efficacy and safety of transepithelial photorefractive keratectomy (TPRK) without mitomycin C as treatment for femtosecond laser in situ keratomileusis (FS-LASIK) corneal flap complications. Methods. Eight patients with corneal flap complications that occurred after FS-LASIK (five with eccentric flaps, two with buttonhole flaps, and one with a thick flap) were included in the study. Patients were treated with TPRK without mitomycin C between two weeks and twelve months after surgery. The postoperative manifest refraction, uncorrected distance visual acuity, and haze formation were assessed during six months of follow-up. Results. The mean manifest refractive spherical and cylinder refraction was 0.16 ± 0.26 and −0.44 ± 0.33 diopters, respectively, at six months postoperatively. The uncorrected distance visual acuity was above 20/25 in all patients after six months of follow-up. No haze formation was detected. Conclusions. TPRK without mitomycin C appears to be a safe and effective treatment for FS-LASIK corneal flap complications.

CD22, a member of Siglec family of sialic acid binding proteins, has restricted expression on B cells. Antibody-based agents targeting CD22 or CD20 on B lymphoma and leukemia cells exhibit clinical efficacy for treating these malignancies, but also attack normal B cells leading to immune deficiency. Here, we report a chemoenzymatic glycocalyx editing strategy to introduce high-affinity and specific CD22 ligands onto NK-92MI and cytokine-induced natural killer cells to achieve tumor-specific CD22 targeting. These CD22-ligand modified cells exhibited significantly enhanced tumor cell binding and killing in vitro without harming healthy B cells. For effective lymphoma cell killing in vivo, we further functionalized CD22 ligand-modified NK-92MI cells with the E-selectin ligand sialyl Lewis X to promote trafficking to bone marrow. The dual-functionalized cells resulted in the efficient suppression of B lymphoma in a xenograft model. Our results suggest that nature killer cells modified with glycan ligands to CD22 and selectins promote both targeted killing of B lymphoma cells and improved trafficking to sites where the cancer cells reside, respectively.

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19–89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

Precise and automated analysis of site-specific O-glycosylation on single proteins is crucial for comprehensive characterization of some important glycoproteins, such as tumor biomarkers and recombinant drug proteins. Mass spectrometry has been proven to be a powerful technique for protein sequencing and N-glycosylation analysis. However, challenges remain in developing computational tools for intact O-glycopeptide analysis, which has greatly hindered the development of mass-spectrometry-based O-glycosylation analysis. Herein, an integrated strategy together with a dedicated automated computational tool termed AOGP was developed for intact O-glycopeptide analysis on single proteins. AOGP utilized de novo sequencing for O-glycans and a database search strategy for peptide backbones. The false discovery rate (FDR) of the identification results was controlled and validated by a mixed Gaussian distribution estimation method. AOGP exhibited superior performance in identifying intact O-glycopeptides of the human erythropoietin with a total of 188 O-glycopeptide spectra reported under 1% FDR. AOGP is developed in Python, is fully open-sourced, and is equipped with a user-friendly interface. Such an easy-operating and robust tool would greatly facilitate O-glycosylation analysis on single proteins in tumor biomarker and recombinant drug protein development.

Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies., Data independent acquisition (DIA) proteomics provides deep coverage and high quantitative accuracy, but is not yet well established in glycoproteomics. Here, the authors develop a DIA-based glycoproteomics workflow with stringent statistical controls to enable accurate glycopeptide identification.

The heterogeneity and low abundance of protein glycosylation present challenging barriers to the analysis of intact glycopeptides, which is key to comprehensively understanding the role of glycosylation in an organism. Efficient and specific enrichment of intact glycopeptides could help greatly with this problem. Here, we propose a new enrichment strategy using a boronic acid (BA)-functionalized mesoporous graphene-silica composite (denoted as GO@mSiO2-GLYMO-APB) for isolating intact glycopeptides from complex biological samples. The merits of this composite, including high surface area and synergistic effect from size exclusion functionality of mesoporous material, hydrophilic interaction of silica, and the reversible covalent binding with BA, enable the effective and specific enrichment of both intact N- and O-glycopeptides. The results from the enrichment performance of the strategy evaluated by standard glycoproteins and the application to global N- and O-glycosylation analyses in human serum indicate the robustness and potential of the strategy for intact glycopeptide analysis.

Glycoproteome profiling (glycoproteomics) is a powerful yet analytically challenging research tool. The complex tandem mass spectra generated from glycopeptide mixtures require sophisticated analysis pipelines for structural determination. Diverse software aiding the process have appeared, but their relative performance remains untested. Conducted through the HUPO Human Proteome Project – Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates the performance of informatics solutions for system-wide glycopeptide analysis. Mass spectrometry-based glycoproteomics datasets from human serum were shared with all teams. The relative team performance forN- andO-glycopeptide data analysis was comprehensively established and validated through orthogonal performance tests. Excitingly, several high-performance glycoproteomics informatics solutions were identified. While the study illustrated that significant informatics challenges remain, as indicated by a high discordance between annotated glycopeptides, lists of high-confidence (consensus) glycopeptides were compiled from the standardised team reports. Deep analysis of the performance data revealed key performance-associated search variables and led to recommendations for improved “high coverage” and “high accuracy” glycoproteomics search strategies. This study concludes that diverse software for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies, and specifies key variables that may guide future software developments and assist informatics decision-making in glycoproteomics.

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools., Graphical abstract, Highlights • Summarize the development of software tools for intact glycopeptide analysis. • Survey the MS acquisition strategies for glycopeptide spectrum acquisition. • Conclude the quality control methods for glycopeptide-spectrum matching. • Show the application of intact glycopeptide analysis in glycoproteomic research., In Brief This article provides a systematic review of the most recent MS-based strategies and corresponding software tools for the analysis of intact glycopeptides, particularly intact N-glycopeptides, reported in the last decade, including the process of identifying N-glycopeptides from MS data, the existing methods of MS data acquisition and interpretation, the quality control methods, the display of results, and the software applications.

We present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A novel glycan ion-indexing algorithm developed in this work for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing the accuracies and sensitivities. By combining electron-based dissociation spectra, pGlyco3 integrates a fast, dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization (SSGL). Our evaluation based on synthetic and natural glycopeptides showed that the SSGL probabilities estimated by pGlycoSite were proved to be appropriate to localize site-specific glycans. With pGlyco3, we found that N-glycopeptides and O-mannose glycopeptides in yeast samples were extensively modified by ammonia adducts on Hex (aH) and verified the aH-glycopeptide identifications based on released N-glycans and15N/13C-labeled data. Thus pGlyco3, which is freely available onhttps://github.com/pFindStudio/pGlyco3/releases, is an accurate and flexible tool to identify glycopeptides and modified saccharide units.

Global in-depth analysis of N-glycosylation, as the most complex post-translational modification of proteins, is requiring methods being as sensitive, selective and reliable as possible. Here, an enhanced strategy for N-glycomics is presented comprising optimized sample preparation yielding enhanced glycoprotein recovery and permethylation efficiency, isotopic labelling for data quality control and relative quantification, integration of new N-glycan libraries (human and mouse), newly developed R-scripts matching experimental MS1 data to theoretical N-glycan compositions and bundled sequencing algorithms for MS2-based structural identification to ultimately enhance the coverage and accuracy of N-glycans. With this strategy the numbers of identified N-glycans are more than doubled compared with previous studies, exemplified by etanercept (more than 3-fold) and chicken ovalbumin (more than 2-fold) at nanogram level. The power of this strategy and applicability to biological samples is further demonstrated by comparative N-glycomics of human acute promyelocytic leukemia cells before and after treatment with all-trans retinoic acid, showing that N-glycan biosynthesis is slowed down and 57 species are significantly altered in response to the treatment. This improved analytical platform enables deep and accurate N-glycomics for glycobiological research and biomarker discovery.

A powerful and fast glycopeptide/glycan enrichment method is critical for the efficiency and throughput of mass spectrometry (MS)-based glycoproteomic and glycomic analyses, especially for large-scale sample analysis. Here, we report an ultrafast and effective method for both intact N-glycopeptide and N-glycan enrichment and apply it to human serum samples. In this method, a natural hydrophilic material, bacterial cellulose (BC), was adopted and fully optimized for enrichment. This method offers the following advantages: (i) The enrichment material has natural hydrophilicity and is low-cost, biocompatible, biodegradable and easily accessible; (ii) the whole enrichment procedure is remarkably simple and fast. It takes only 10 min for intact glycopeptides/glycans to be easily purified from mixtures; (iii) the specificity of this method is over 94% for both glycan and glycopeptide enrichment; and (iv) the outstanding specificity of this technique enables high isolation efficiency for the enrichment of both intact glycopeptides and glycans. A total of 36 N-glycans and 31 N-glycopeptides were identified from human immunoglobulin G (IgG). The glycan and glycopeptide absorption capacity of BC was as high as 333 μg/mg and 250 μg/mg (IgG/BC) respectively. The selectivity for glycan and glycopeptide enrichment reached 1:100 (IgG/bovine serum albumin (BSA), molar ratio) and 1:200 (maltoheptaose (DP7)/BSA, molar ratio), respectively. Furthermore, a total of 159 N-glycans and 523 N-glycopeptides were identified in human serum by using this method. Overall, the BC-based enrichment method we present here provides an ultrafast and highly efficient method for the enrichment of both N-glycopeptides and N-glycans in complex samples and shows great potential in large-scale glycoproteomic and glycomic analyses.

Precise and automated analysis of site-specific

Efficient detection of aberrant glycoproteins in serum is particularly important for biomarker discovery. However, direct quantitation of glycoproteins in serum remains technically challenging because of the extraordinary complexity of the serum proteome. In the current work, we proposed a straightforward and highly efficient strategy by using the nonglycopeptides releasing from the specifically enriched glycoproteins for targeted glycoprotein quantification. With this so-called nonglycopeptide-based mass spectrometry (NGP-MS) strategy, a powerful and nondiscriminatory pipeline for hepatocellular carcinoma (HCC) glycoprotein biomarker discovery, verification, and validation has been developed. First, a data set of 234 NGPs was strictly established for multiple-reaction monitoring (MRM) quantification in serum. Second, the NGPs enriched from 20 HCC serum mixtures and 20 normal serum mixtures were labeled with mTRAQ reagents (Δ0 and Δ8, respectively) to find the differentially expressed glycoproteins in HCC. A total of 97 glycoprotein candidates were preliminarily screened and submitted for absolute quantitation with NGP-based stable-isotope-labeled (SID)-MRM in the individual samples of 38 HCC serum and 24 normal controls. Finally, 21 glycoproteins were absolutely quantified with high quality. The diagnostic sensitivity results showed that three glycoproteins, β-2-glycoprotein 1 (APOH), α-1-acid glycoprotein 2 (ORM2), and complement C3 (C3), could be used for the discrimination between HCC patients and healthy people. A novel glycoprotein biomarker panel [APOH, ORM2, C3, and α-fetoprotein (AFP)] has proven to outperform AFP, the known HCC serum biomarker, alone, in this study. We believe that this strategy and the panel of glycoproteins might hold great clinical value for HCC detection in the future.

The emitter clogging is the most common hardware failure of nano-electrospray ionization, to improve the durability and electrospray stability of fused silica emitters, we demonstrate a means of fabricating nano-electrospray emitters with controllable aperture size and gradually-narrowed channel on the tip. We simulated the fluid morphologies in the emitter channels by computational fluid dynamics and found more stable flow on aperture-controllable nano-electrospray emitter. Besides, we found the unstable flow sections of commercial emitters match the actual clogging sections very well, indicating the main cause of emitter clogging is unstable flow. We further tested the emitters by nano-LC-MS based proteome analysis. Compared with the commercial emitter, aperture-controllable nano-electrospray emitters promoted the total ion chromatogram intensity by 25%, the number of identified proteins by 6.58%, and the number of identified peptides by 7.87%. In total, 989 proteins were identified from 1 μg of extracted mouse cardiac proteins. After the optimization by using mouse samples, we analyzed clinical auricular dextral tissues from patients undergoing cardiac surgery and found 16 proteins related to atrial fibrillation. Overall, aperture-controllable nano-electrospray emitter exhibits better sensitivity and reproducibility in the application of nano-LC-MS cardiac proteome analysis.

N-glycosylation is deeply involved in many biological processes, and approximately 50% of mammalian proteins are predicted to be glycosylated. Many large-scale studies have been carried out to reveal the glycosylation status involved in different physiological pathologies across species. However, the lack of a highly specific and high-throughput N-glycosylated enrichment method not only results in extended time requirements but also limits the depth of mapping when handling a large number of samples. In this study, we firstly optimized traditional zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) enrichment and found that using of 70% acetonitrile (ACN), 0.1% trifluoroacetic acid (TFA) as the enrichment buffer, 2800 g as the washing speed and 600 μL as the washing volume achieved the best specificity, which is higher than 75%. On this basis, we developed a multi-parallel enrichment strategy assisted by a filter-coated 96-well plate, which achieved high specificity and high throughput simultaneously. This strategy allowed us to enrich large numbers of fractionated samples from hepatocellular carcinoma (HCC) cell lines in less than 2 h. Its good specificity helped us achieve in-depth mapping of the N-glycoproteome in metastatic HCC cell lines. A total of 5466 N-glycosites from 2383 glycoproteins were identified, among which 1900 N-glycosites were unannotated in UniProt. The in-depth glycoproteome mapping provides insight into the N-glycosylation status in HCC cell lines with differences in metastatic potential and contributes to biomarker discovery.

PNGase F-catalyzed glycosylation site (18)O-labeling is a widely used method for glycoprotein quantitation owing to its efficiency and simplicity. However, PNGase F-catalyzed glycan (18)O-labeling, which offers advantages for glycomics, has not yet been developed. In this study, PNGase F-mediated incorporation of (18)O into glycans during the N-glycan release from glycoproteins by PNGase F was finally realized, named as PCGOL (PNGase F-catalyzed glycan (18)O-labeling), which offers a potential strategy for relative glycan quantitation. This new method showed good linearity and high reproducibility within at least 2 orders of magnitude in the dynamic range. Furthermore, PCGOL combined with our previously developed TOSIL method (tandem (18)O stable isotope labeling for N-glycoproteome quantitation) can be used for comprehensive N-glycosylation quantification, achieving simultaneous quantification of glycans, glycopeptides and glycoproteins in a single workflow, which was also used to analyze glycosylation changes in immunoglobulin G (IgG) associated with hepatocellular carcinoma in the present work.

GREDIL for quantitative N-glycomics largely improves the stability of N-glycan 18O-labeling and greatly decreases the interference of isotopic cluster overlap.

The precision prediction of peptide retention time (RT) plays an increasingly important role in liquid chromatography–tandem mass spectrometry (LC–MS/MS) based proteomics. Owing to the high reproducibility of liquid chromatography, RT prediction provides promising information for both identification and quantification experiment design. In this work, we present a Locus-specific Retention Predictor (LsRP) for precise prediction of peptide RT, which is based on amino acid locus information and Support Vector Regression (SVR) algorithm. Corresponding to amino acid locus, each peptide sequence was converted to a featured locus vector consisting of zeros and ones. With locus vector information from LC-MS/MS data sets, an SVR computational process was trained and evaluated. LsRP finally provided a prediction correlation coefficient of 0.95~0.99. We compared our method with two common predictors. Results showed that LsRP outperforms these methods and tracked up to 30% extra peptides in an extraction RT window of 2 min. A new strategy by combining LsRP and calibration peptide approach was then proposed, which open up new opportunities for precision proteomics.

Introduction: The liver is an important organ in humans. Hepatocellular carcinoma (HCC) is one of the deadliest cancers in the world. Progress in the Human Liver Proteome Project (HLPP) has improved understanding of the liver and the liver cancer proteome.Areas covered: Here, we summarize the recent progress in liver proteome modification profiles, proteomic studies in liver cancer, proteomic study in the search for novel liver cancer biomarkers and drug targets, and progress of the Chromosome Centric Human Proteome Project (CHPP) in the past five years in the Institutes of Biomedical Sciences (IBS) of Fudan University.Expert commentary: Recent advances and findings discussed here provide great promise of improving the outcome of patients with liver cancer.

Efficient glycopeptides enrichment prior to mass spectrometry analysis is essential for glycoproteome study. ZIC-HILIC (zwitterionic hydrophilic interaction liquid chromatography) based glycopeptides enrichment approaches have been attracting more attention for several benefits like easy operating, high enrichment specificity and intact glycopeptide retained. In this study, Poly (amidoamine) dendrimer (PAMAM) was adopted for the synthesis of zwitterionically functionalized (ZICF) materials for glycopeptide enrichment. The multiple branched structure and good solubility of ZICF-PAMAM enables a sufficient interaction with glycopeptides. The ZICF-PAMAM combined with the FASP-mode enrichment strategy exhibits more superior performance compared with the existing methods. It has the minimum detectable concentration of femtomolar level and high recovery rate of over 90.01%, and can efficiently enrich glycopeptides from complex biological samples even for merely 0.1 μL human serum. The remarkable glycopeptides enrichment capacity of ZICF-PAMAM highlights the potential application in in-depth glycoproteome research, which may open up new opportunities for the development of glycoproteomics.

Confident characterization of the microheterogeneity of protein glycosylation through identification of intact glycopeptides remains one of the toughest analytical challenges for glycoproteomics. Recently proposed mass spectrometry (MS)-based methods still have some defects such as lack of the false discovery rate (FDR) analysis for the glycan identification and lack of sufficient fragmentation information for the peptide identification. Here we proposed pGlyco, a novel pipeline for the identification of intact glycopeptides by using complementary MS techniques: 1) HCD-MS/MS followed by product-dependent CID-MS/MS was used to provide complementary fragments to identify the glycans and a novel target-decoy method was developed to estimate the false discovery rate of the glycan identification; 2) data-dependent acquisition of MS3 for some most intense peaks of HCD-MS/MS was used to provide fragments to identify the peptide backbones. By integrating HCD-MS/MS, CID-MS/MS and MS3, intact glycopeptides could be confidently identified. With pGlyco, a standard glycoprotein mixture was analyzed in the Orbitrap Fusion and 309 non-redundant intact glycopeptides were identified with detailed spectral information of both glycans and peptides.

The Human Disease Glycomics/Proteome Initiative (HGPI) is an activity in the Human Proteome Organization (HUPO) supported by leading researchers from international institutes and aims at development of disease-related glycomics/glycoproteomics analysis techniques. Since 2004, the initiative has conducted three pilot studies. The first two were N- and O-glycan analyses of purified transferrin and immunoglobulin-G and assessed the most appropriate analytical approach employed at the time. This paper describes the third study, which was conducted to compare different approaches for quantitation of N- and O-linked glycans attached to proteins in crude biological samples. The preliminary analysis on cell pellets resulted in wildly varied glycan profiles, which was probably the consequence of variations in the pre-processing sample preparation methodologies. However, the reproducibility of the data was not improved dramatically in the subsequent analysis on cell lysate fractions prepared in a specified method by one lab. The study demonstrated the difficulty of carrying out a complete analysis of the glycome in crude samples by any single technology and the importance of rigorous optimization of the course of analysis from preprocessing to data interpretation. It suggests that another collaborative study employing the latest technologies in this rapidly evolving field will help to realize the requirements of carrying out the large-scale analysis of glycoproteins in complex cell samples.

O-linked β-N-acetylglucosamine (O-GlcNAc) is an important post-translational modification (PTM) consisting of a single N-acetylglucosamine moiety attached via an O-β-glycosidic linkage to serine and threonine residues. Glycosylation with O-GlcNAc occurs on myriad nuclear and cytosolic proteins from almost all functional classes. However, with respect to O-GlcNAcylated proteins special in mitochondria, little attention has been paid. In this study, we combined mass spectrometry and immunological methods to perform global exploration of O-GlcNAcylated proteins specific in mitochondria of rat liver. First, highly purified mitochondrial proteins were obviously shown to be O-GlcNAcylated by immunoblot profiling. Then, β-elimination followed by Michael Addition with Dithiothreitol (BEMAD) treatment and LC-MS/MS were performed to enrich and identify O-GlcNAcylated mitochondrial proteins, resulting in an unambiguous assignment of 14 O-GlcNAcylation sites, mapping to 11 O-GlcNAcylated proteins. Furthermore, the identified O-GlcNAcylated mitochondrial proteins were fully validated by both electron transfer dissociation tandem mass spectrometry (ETD/MS/MS) and western blot. Thus, for the first time, our study definitely not only identified but also validated that some mitochondrial proteins in rat liver are O-GlcNAcylated. Interestingly, all of these O-GlcNAcylated mitochondrial proteins are enzymes, the majority of which are involved in a wide variety of biological processes, such as urea cycle, tricarboxylic acid cycle and lipid metabolism, indicating a role for protein O-GlcNAcylation in mitochondrial function.

Playing an important role in a broad range of biological and pathological processes, sialylation has been drawing wide interest. The efficient sialoglycopeptides enrichment methods are therefore attracting considerable attention. In this paper, we first compared two conventional enrichment methods, lectin and TiO(2), and analyzed their characteristics. Furthermore, considering the highly negatively charged nature of sialic acids, we developed a new strategy, peptide immobilized pH gradient isoelectric focusing (IPG-IEF) assisted TiO(2) chromatography (PIAT), for the highly efficient enrichment of sialoglycopeptides. In this method, peptides were first separated into 24 fractions using peptide IPG-IEF. Sialoglycopeptides were relatively concentrated in low-pH fractions of the immobilized pH strips and were captured using TiO(2) chromatography. As a result, 614 N-glycosylation sites were identified in 582 sialoglycopeptides within 322 sialoglycoproteins from rat liver using PIAT. To our knowledge, this work represents one of the most comprehensive sialoglycoproteomic analyses in general and exhibits the largest database of sialoglycoproteome in rat liver currently. So the new strategy introduced here exhibits high efficiency and universality in the sialoglycopeptide enrichment, and is a powerful tool for sialoglycoproteome exploration.