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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38925550 DOI: 10.1002/mas.21873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/05/2024] [Accepted: 02/12/2024] [Indexed: 06/28/2024]
Abstract
The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.
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Garapati K, Budhraja R, Saraswat M, Kim J, Joshi N, Sachdeva GS, Jain A, Ligezka AN, Radenkovic S, Ramarajan MG, Udainiya S, Raymond K, He M, Lam C, Larson A, Edmondson AC, Sarafoglou K, Larson NB, Freeze HH, Schultz MJ, Kozicz T, Morava E, Pandey A. A complement C4-derived glycopeptide is a biomarker for PMM2-CDG. JCI Insight 2024; 9:e172509. [PMID: 38587076 PMCID: PMC7615924 DOI: 10.1172/jci.insight.172509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 02/15/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUNDDiagnosis of PMM2-CDG, the most common congenital disorder of glycosylation (CDG), relies on measuring carbohydrate-deficient transferrin (CDT) and genetic testing. CDT tests have false negatives and may normalize with age. Site-specific changes in protein N-glycosylation have not been reported in sera in PMM2-CDG.METHODSUsing multistep mass spectrometry-based N-glycoproteomics, we analyzed sera from 72 individuals to discover and validate glycopeptide alterations. We performed comprehensive tandem mass tag-based discovery experiments in well-characterized patients and controls. Next, we developed a method for rapid profiling of additional samples. Finally, targeted mass spectrometry was used for validation in an independent set of samples in a blinded fashion.RESULTSOf the 3,342 N-glycopeptides identified, patients exhibited decrease in complex-type N-glycans and increase in truncated, mannose-rich, and hybrid species. We identified a glycopeptide from complement C4 carrying the glycan Man5GlcNAc2, which was not detected in controls, in 5 patients with normal CDT results, including 1 after liver transplant and 2 with a known genetic variant associated with mild disease, indicating greater sensitivity than CDT. It was detected by targeted analysis in 2 individuals with variants of uncertain significance in PMM2.CONCLUSIONComplement C4-derived Man5GlcNAc2 glycopeptide could be a biomarker for accurate diagnosis and therapeutic monitoring of patients with PMM2-CDG and other CDGs.FUNDINGU54NS115198 (Frontiers in Congenital Disorders of Glycosylation: NINDS; NCATS; Eunice Kennedy Shriver NICHD; Rare Disorders Consortium Disease Network); K08NS118119 (NINDS); Minnesota Partnership for Biotechnology and Medical Genomics; Rocket Fund; R01DK099551 (NIDDK); Mayo Clinic DERIVE Office; Mayo Clinic Center for Biomedical Discovery; IA/CRC/20/1/600002 (Center for Rare Disease Diagnosis, Research and Training; DBT/Wellcome Trust India Alliance).
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Affiliation(s)
- Kishore Garapati
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Manipal Academy of Higher Education (MAHE), Manipal, India
| | - Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Mayank Saraswat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jinyong Kim
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Neha Joshi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Manipal Academy of Higher Education (MAHE), Manipal, India
| | - Gunveen S. Sachdeva
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Manipal Academy of Higher Education (MAHE), Manipal, India
| | - Anu Jain
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Madan Gopal Ramarajan
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Manipal Academy of Higher Education (MAHE), Manipal, India
| | - Savita Udainiya
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Manipal Academy of Higher Education (MAHE), Manipal, India
| | - Kimiyo Raymond
- Biochemical Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Miao He
- Department of Pathology and Laboratory Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Christina Lam
- Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, Washington, USA
- Division of Genetic Medicine, Department of Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
| | | | - Andrew C. Edmondson
- Division of Human Genetics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Kyriakie Sarafoglou
- Division of Pediatric Endocrinology, Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota, USA
- Department of Experimental and Clinical Pharmacology, University of Minnesota School of Pharmacy, Minneapolis, Minnesota, USA
| | - Nicholas B. Larson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Hudson H. Freeze
- Sanford Children’s Health Research Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Matthew J. Schultz
- Biochemical Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Tamas Kozicz
- Department of Clinical Genomics and
- Biochemical Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Anatomy, University of Pécs Medical School, Pécs, Hungary
- Department of Genomics and Genetic Sciences, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA
| | - Eva Morava
- Department of Clinical Genomics and
- Biochemical Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Anatomy, University of Pécs Medical School, Pécs, Hungary
- Department of Genomics and Genetic Sciences, Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
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He K, Baniasad M, Kwon H, Caval T, Xu G, Lebrilla C, Hommes DW, Bertozzi C. Decoding the glycoproteome: a new frontier for biomarker discovery in cancer. J Hematol Oncol 2024; 17:12. [PMID: 38515194 PMCID: PMC10958865 DOI: 10.1186/s13045-024-01532-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 03/04/2024] [Indexed: 03/23/2024] Open
Abstract
Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.
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Affiliation(s)
- Kai He
- James Comprehensive Cancer Center, The Ohio State University, Columbus, USA.
| | | | - Hyunwoo Kwon
- James Comprehensive Cancer Center, The Ohio State University, Columbus, USA
| | | | - Gege Xu
- InterVenn Biosciences, South San Francisco, USA
| | - Carlito Lebrilla
- Department of Biochemistry and Molecular Medicine, UC Davis Health, Sacramento, USA
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4
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Xie Y, Liu X, Zhao C, Chen S, Wang S, Lin Z, Robison FM, George BM, Flynn RA, Lebrilla CB, Garcia BA. Development and application of GlycanDIA workflow for glycomic analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.12.584702. [PMID: 38559279 PMCID: PMC10980037 DOI: 10.1101/2024.03.12.584702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Thus, while the significance of glycosylation is well established, a lack of accessible methods to characterize glycans has hindered the ability to understand their biological functions. Mass spectrometry (MS)-based methods have generally been at the core of most glycan profiling efforts; however, modern data-independent acquisition (DIA), which could increase sensitivity and simplify workflows, has not been benchmarked for analyzing glycans. Herein, we developed a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and accuracy. The GlycanDIA workflow combined higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and the accuracy in quantification compared to conventional data-dependent acquisition (DDA)-based glycomics. To facilitate its use, we also developed a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification and quantification from DIA data. The results showed that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity, we performed experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we found that RNA-glycans have specific forms as compared to protein-glycans and are also tissue-specific differences, suggesting distinct functions in biological processes. Overall, GlycanDIA can provide comprehensive information for glycan identification and quantification, enabling researchers to obtain in-depth and refined details on the biological roles of glycosylation.
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Affiliation(s)
- Yixuan Xie
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States
- Department of Chemistry, University of California, Davis, Davis, California, United States
| | - Xingyu Liu
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States
| | - Chenfeng Zhao
- Department of Computer Science & Engineering, Washington University, St. Louis, Missouri, United States
| | - Siyu Chen
- Department of Chemistry, University of California, Davis, Davis, California, United States
| | - Shunyang Wang
- Department of Chemistry, University of California, Davis, Davis, California, United States
| | - Zongtao Lin
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States
| | - Faith M Robison
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States
| | - Benson M George
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts, United States
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, United States
| | - Ryan A Flynn
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts, United States
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, United States
| | - Carlito B Lebrilla
- Department of Chemistry, University of California, Davis, Davis, California, United States
- Department of Biochemistry, University of California, Davis, Davis, California, United States
| | - Benjamin A Garcia
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States
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Lazari LC, Santiago VF, de Oliveira GS, Mule SN, Angeli CB, Rosa-Fernandes L, Palmisano G. Glycosort: A Computational Solution to Post-process Quantitative Large-Scale Intact Glycopeptide Analyses. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:23-32. [PMID: 38409414 DOI: 10.1007/978-3-031-50624-6_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Protein glycosylation is a post-translational modification involving the addition of carbohydrates to proteins and plays a crucial role in protein folding and various biological processes such as cell recognition, differentiation, and immune response. The vast array of natural sugars available allows the generation of plenty of unique glycan structures in proteins, adding complexity to the regulation and biological functions of glycans. The diversity is further increased by enzymatic site preferences and stereochemical conjugation, leading to an immense amount of different glycan structures. Understanding glycosylation heterogeneity is vital for unraveling the impact of glycans on different biological functions. Evaluating site occupancies and structural heterogeneity aids in comprehending glycan-related alterations in biological processes. Several software tools are available for large-scale glycoproteomics studies; however, integrating identification and quantitative data to assess heterogeneity complexity often requires extensive manual data processing. To address this challenge, we present a python script that automates the integration of Byonic and MaxQuant outputs for glycoproteomic data analysis. The script enables the calculation of site occupancy percentages by glycans and facilitates the comparison of glycan structures and site occupancies between two groups. This automated tool offers researchers a means to organize and interpret their high-throughput quantitative glycoproteomic data effectively.
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Affiliation(s)
- Lucas C Lazari
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Veronica Feijoli Santiago
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Gilberto S de Oliveira
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Simon Ngao Mule
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Claudia B Angeli
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Livia Rosa-Fernandes
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
- Centre for Motor Neuron Disease Research, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Giuseppe Palmisano
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil.
- School of Natural Sciences, Faculty of Science and Engineering, Sydney, Australia.
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6
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Gutierrez Reyes CD, Sanni A, Adeniyi M, Mogut D, Najera Gonzalez HR, Ahmadi P, Atashi M, Onigbinde S, Mechref Y. Targeted Glycoproteomics Analysis Using MRM/PRM Approaches. Methods Mol Biol 2024; 2762:231-250. [PMID: 38315369 DOI: 10.1007/978-1-0716-3666-4_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
MS-target analyses are frequently utilized to analyze and validate structural changes of biomolecules across diverse fields of study such as proteomics, glycoproteomics, glycomics, lipidomics, and metabolomics. Targeted studies are commonly conducted using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) techniques. A reliable glycoproteomics analysis in intricate biological matrices is possible with these techniques, which streamline the analytical workflow, lower background interference, and enhance selectivity and specificity.
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Affiliation(s)
| | - Akeem Sanni
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Moyinoluwa Adeniyi
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Damir Mogut
- Department of Food Biochemistry, Faculty of Food Science, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Hector R Najera Gonzalez
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, USA
| | - Parisa Ahmadi
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Mojgan Atashi
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Sherifdeen Onigbinde
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Yehia Mechref
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA.
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7
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Zhu Y. Plasma/Serum Proteomics based on Mass Spectrometry. Protein Pept Lett 2024; 31:192-208. [PMID: 38869039 PMCID: PMC11165715 DOI: 10.2174/0109298665286952240212053723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/22/2024] [Accepted: 01/31/2024] [Indexed: 06/14/2024]
Abstract
Human blood is a window of physiology and disease. Examination of biomarkers in blood is a common clinical procedure, which can be informative in diagnosis and prognosis of diseases, and in evaluating treatment effectiveness. There is still a huge demand on new blood biomarkers and assays for precision medicine nowadays, therefore plasma/serum proteomics has attracted increasing attention in recent years. How to effectively proceed with the biomarker discovery and clinical diagnostic assay development is a question raised to researchers who are interested in this area. In this review, we comprehensively introduce the background and advancement of technologies for blood proteomics, with a focus on mass spectrometry (MS). Analyzing existing blood biomarkers and newly-built diagnostic assays based on MS can shed light on developing new biomarkers and analytical methods. We summarize various protein analytes in plasma/serum which include total proteome, protein post-translational modifications, and extracellular vesicles, focusing on their corresponding sample preparation methods for MS analysis. We propose screening multiple protein analytes in the same set of blood samples in order to increase success rate for biomarker discovery. We also review the trends of MS techniques for blood tests including sample preparation automation, and further provide our perspectives on their future directions.
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Affiliation(s)
- Yiying Zhu
- Department of Chemistry, Tsinghua University, Beijing, China
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8
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Ma M, Li M, Zhu Y, Zhao Y, Wu F, Wang Z, Feng Y, Chiang HY, Patankar MS, Chang C, Li L. 6-Plex mdSUGAR Isobaric-Labeling Guide Fingerprint Embedding for Glycomics Analysis. Anal Chem 2023; 95:17637-17645. [PMID: 37982459 PMCID: PMC10794169 DOI: 10.1021/acs.analchem.3c03342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex mdSUGAR isobaric-labeling guide fingerprint embedding (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex mdSUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 103 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.
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Affiliation(s)
- Min Ma
- School of Pharmacy, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
| | - Miyang Li
- Department of Chemistry, University of Wisconsin–Madison, Madison, Wisconsin 53706, USA
| | - Yinlong Zhu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
- Chongqing Key Laboratory on Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yingyi Zhao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Feixuan Wu
- School of Pharmacy, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
| | - Zicong Wang
- School of Pharmacy, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
| | - Yu Feng
- School of Pharmacy, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
| | - Hung-Yu Chiang
- Biophysics Program, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
| | - Manish S. Patankar
- Department of Obstetrics and Gynecology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
| | - Cheng Chang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
- Research Unit of Proteomics Driven Cancer Precision Medicine, Chinese Academy of Medical Sciences, Beijing 102206, China
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin–Madison, Madison, Wisconsin 53705, USA
- Department of Chemistry, University of Wisconsin–Madison, Madison, Wisconsin 53706, USA
- Lachman Institute for Pharmaceutical Development, School of Pharmacy, University of Wisconsin-Madison, Madison, WI 53705, USA
- Wisconsin Center for NanoBioSystems, School of Pharmacy, University of Wisconsin-Madison, Madison, WI 53705, USA
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Luo M, Su T, Cheng Q, Zhang X, Cai F, Yin Z, Li F, Yang H, Liu F, Zhang Y. GlycoTCFM: Glycoproteomics Based on Two Complementary Fragmentation Methods Reveals Distinctive O-Glycosylation in Human Sperm and Seminal Plasma. J Proteome Res 2023; 22:3833-3842. [PMID: 37943980 DOI: 10.1021/acs.jproteome.3c00489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Human semen, consisting of spermatozoa (sperm) and seminal plasma, represents a special clinical sample type in human body fluid. Protein glycosylation in sperm and seminal plasma plays key roles in spermatogenesis, maturation, capacitation, sperm-egg recognition, motility of sperm, and fertilization. In this study, we profiled the most comprehensive O-glycoproteome map of human sperm and seminal plasma using our recently presented Glycoproteomics based on Two Complementary Fragmentation Methods (GlycoTCFM). We showed that sperm and seminal plasma contain many novel and distinctive O-glycoproteins, which are mostly located in the extracellular region (seminal plasma) and sperm membrane, enriched in the biological processes of cell adhesion and angiogenesis, and mainly involved in multiple biological functions including extracellular matrix structural constituents and binding. Based on GlycoTCFM, we created a comprehensive human sperm and seminal plasma O-glycoprotein database that contains 371 intact O-glycopeptides and 202 O-glycosites from 68 O-glycoproteins. Interestingly, 105 manually confirmed O-glycosites from 25 O-glycoproteins were reported for the first time, and they were mainly modified by core 1 O-glycans. We also found that three highly abundant, highly complex, and highly O-glycosylated proteins (semenogelin-1, semenogelin-2, and equatorin) may play important roles in sperm or seminal plasma composition and function. These data deepen our knowledge about O-glycosylation in sperm and seminal plasma and lay the foundation for the functional study of O-glycoproteins in male infertility.
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Affiliation(s)
- Mengqi Luo
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Tao Su
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Qingyuan Cheng
- Human Sperm Bank, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Xue Zhang
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Fei Cai
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Zaiwen Yin
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Fuping Li
- Human Sperm Bank, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Hao Yang
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Fang Liu
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yong Zhang
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China
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10
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Jiang P, Peng W, Zhao J, Goli M, Huang Y, Li Y, Mechref Y. Glycan/Protein-Stable Isotope Labeling in Cell Culture for Enabling Concurrent Quantitative Glycomics/Proteomics/Glycoproteomics. Anal Chem 2023; 95:16059-16069. [PMID: 37843510 DOI: 10.1021/acs.analchem.3c00247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
The complexity and heterogeneity of protein glycosylation present an analytical challenge to the studies of characterization and quantitation. Various LC-MS-based quantitation strategies have emerged in recent decades. Metabolic stable isotope labeling has been developed to enhance the accurate LC/MS-based quantitation between different cell lines. Stable isotope labeling by amino acids in a cell culture (SILAC) is the most widely used metabolic labeling method in proteomic analysis. However, it can only label the peptide backbone and is thus limited in glycomic studies. Here, we present a metabolic isotope labeling strategy, named GlyProSILC (Glycan Protein Stable Isotope Labeling in Cell Culture), that can label both the glycan motif and peptide backbone from the same batch of cells. It was performed by feeding cells with a heavy medium containing amide-15N-glutamine, 13C6-arginine (Arg6), and 13C6-15N2-lysine (Lys8). No significant change of cell line metabolism after GlyProSILC labeling was observed based on transcriptomic, glycomic, and proteomic data. The labeling conditions, labeling efficiency, and quantitation accuracy were investigated. After quantitation correction, we simultaneously quantified 62 N-glycans, 574 proteins, and 344 glycopeptides using the same batch of mixed 231BR/231 cell lines. So far, GlyProSILC provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.
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Affiliation(s)
- Peilin Jiang
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409, United States
| | - Wenjing Peng
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409, United States
| | - Jingfu Zhao
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409, United States
| | - Mona Goli
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409, United States
| | - Yifan Huang
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409, United States
| | - Yunxiang Li
- Division of Chemistry and Biochemistry, Texas Woman's University, Denton, Texas 76204, United States
| | - Yehia Mechref
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409, United States
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11
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Lin T, Chen Z, Luo M, Zhao Y, Zeng W, Zheng S, Su T, Zhong Y, Wang S, Jin Y, Hu L, Zhao W, Li J, Wang X, Wu C, Li D, Liu F, Li G, Yang H, Zhang Y. Characterization of site-specific N-glycosylation signatures of isolated uromodulin from human urine. Analyst 2023; 148:5041-5049. [PMID: 37667671 DOI: 10.1039/d3an01018j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Abstract
Uromodulin (Umod, Tamm-Horsfall protein) is the most abundant urinary N-glycoprotein produced exclusively by the kidney. It can form filaments to antagonize the adhesion of uropathogens. However, the site-specific N-glycosylation signatures of Umod in healthy individuals and patients with IgA nephropathy (IgAN) remain poorly understood due to the lack of suitable isolation and analytical methods. In this study, we first presented a simple and fast method based on diatomaceous earth adsorption to isolate Umod. These isolated glycoproteins were digested by trypsin and/or Glu-C. Intact N-glycopeptides with or without HILIC enrichment were analyzed using our developed EThcD-sceHCD-MS/MS. Based on the optimized workflow, we identified a total of 780 unique intact N-glycopeptides (7 N-glycosites and 152 N-glycan compositions) from healthy individuals. As anticipated, these glycosites exhibited glycoform heterogeneity. Almost all N-glycosites were modified completely by the complex type, except for one N-glycosite (N275), which was nearly entirely occupied by the high-mannose type for mediating Umod's antiadhesive activity. Then, we compared the N-glycosylation of Umod between healthy controls (n = 9) and IgAN patients (n = 9). The N-glycosylation of Umod in IgAN patients will drastically decrease and be lost. Finally, we profiled the most comprehensive site-specific N-glycosylation map of Umod and revealed its alterations in IgAN patients. Our method provides a high-throughput workflow for characterizing the N-glycosylation of Umod, which can aid in understanding its roles in physiology and pathology, as well as serving as a potential diagnostic tool for evolution of renal tubular function.
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Affiliation(s)
- Tianhai Lin
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
- Department of Urology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Zhuo Chen
- Transplant Center and NHC Key Lab of Transplant Engineering and Immunology, Regenerative Medical Research Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Mengqi Luo
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Yang Zhao
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, China
| | - Wenjuan Zeng
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Shanshan Zheng
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Tao Su
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Yi Zhong
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Shisheng Wang
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Youmei Jin
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Liqiang Hu
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Wanjun Zhao
- Division of Thyroid Surgery, Department of General Surgery of Nursing, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Jiaxu Li
- School of Nursing, Chengde Medical University, Chengde, Hebei 067000, China
| | - Xuanyi Wang
- Mingde College, Zhangjiakou University, Zhangjiakou, Hebei 075000, China
| | - Changwei Wu
- Renal Department and Institute of Nephrology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu 611731, China.
| | - Dapeng Li
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, West China School of Pharmacy, Sichuan University, Chengdu 610041, China
| | - Fang Liu
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Guisen Li
- Renal Department and Institute of Nephrology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu 611731, China.
| | - Hao Yang
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
- Transplant Center and NHC Key Lab of Transplant Engineering and Immunology, Regenerative Medical Research Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yong Zhang
- Department of Nephrology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
- Transplant Center and NHC Key Lab of Transplant Engineering and Immunology, Regenerative Medical Research Center, West China Hospital, Sichuan University, Chengdu 610041, China
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12
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Williamson DL, Nagy G. Coupling Isotopic Shifts with Collision Cross-Section Measurements for Carbohydrate Characterization in High-Resolution Ion Mobility Separations. Anal Chem 2023; 95:13992-14000. [PMID: 37683280 PMCID: PMC10538943 DOI: 10.1021/acs.analchem.3c02619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2023]
Abstract
Herein, we introduce a two-dimensional strategy to better characterize carbohydrate isomers. In a single experiment, we can derive cyclic ion mobility-mass spectrometry (cIMS-MS)-based collision cross-section (CCS) values in conjunction with measuring isotopic shifts through the relative arrival times of light and heavy isotopologues. These isotopic shifts were introduced by permethylating carbohydrates with either light, CH3, or heavy, CD3, labels at every available hydroxyl group to generate a light/heavy pair of isotopologues for every individual species analyzed. We observed that our calculated CCS values, which were exclusively measured for the light isotopologues, were orthogonal to our measured isotopic shifts (i.e., relative arrival time values between heavy and light permethylated isotopologues). Our permethylation-induced isotopic shifts scaled well with increasing molecular weight, up to ∼m/z 1300, expanding the analysis of isotopic shifts to molecules 3-4 times as large as those previously studied. Our presented use of coupling CCS values with the measurement of isotopic shifts in a single cIMS-MS experiment is a proof-of-concept demonstration that our two-dimensional approach can improve the characterization of challenging isomeric carbohydrates. We envision that our presented 2D approach will have broad utility for varying molecular classes as well as being amenable to many forms of derivatization.
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Affiliation(s)
- David L Williamson
- Department of Chemistry, University of Utah, 315 South 1400 East, Room 2020, Salt Lake City, Utah 84112, United States
| | - Gabe Nagy
- Department of Chemistry, University of Utah, 315 South 1400 East, Room 2020, Salt Lake City, Utah 84112, United States
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13
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van der Burgt Y, Wuhrer M. The role of clinical glyco(proteo)mics in precision medicine. Mol Cell Proteomics 2023:100565. [PMID: 37169080 DOI: 10.1016/j.mcpro.2023.100565] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/12/2023] [Accepted: 05/02/2023] [Indexed: 05/13/2023] Open
Abstract
Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.
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Affiliation(s)
- Yuri van der Burgt
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
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14
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Shimoda A, Akiyoshi K. Surface Glycan Profiling of Extracellular Vesicles by Lectin Microarray and Glycoengineering for Control of Cellular Interactions. Pharm Res 2023; 40:795-800. [PMID: 37038008 DOI: 10.1007/s11095-023-03511-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 03/31/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Extracellular vesicles (EVs) are a group of cell-derived membrane vesicles that carry a variety of cargo such as protein, nucleic acids, and lipids, and are secreted by almost all cell types. Functionally, EVs play important roles in physiological and pathological processes such as immune responses and tumor growth through intercellular communication by transferring this molecular information between cells. Therefore, they have potential versatile clinical applications as disease biomarkers and drug delivery carriers. PROBLEM Notably, subpopulations of EVs exhibit distinct characteristics depending on their cell of origin, including the expression of surface glycans, which have been implicated in a variety of cellular processes such as field cancerization, cell recognition, and signal transduction. However, these are features have not been fully exploited because of the difficulty in analyzing these proteins. APPROACH In this paper, we summarize the advancements in glycoengineering and high-performance lectin microarray for high-throughput analysis of EV glycans to generate an index of heterogeneity to identify disease biomarkers, and describe how understanding the function of EVs in disease can enhance their potential application in the clinic.
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Affiliation(s)
- Asako Shimoda
- Department of Polymer Chemistry, Graduate School of Engineering, Kyoto University, Katsura, Nishikyo-Ku, Kyoto, 615-8510, Japan
| | - Kazunari Akiyoshi
- Department of Polymer Chemistry, Graduate School of Engineering, Kyoto University, Katsura, Nishikyo-Ku, Kyoto, 615-8510, Japan.
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15
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Mastrangeli R, Satwekar A, Bierau H. Innovative Metrics for Reporting and Comparing the Glycan Structural Profile in Biotherapeutics. Molecules 2023; 28:molecules28083304. [PMID: 37110538 PMCID: PMC10143042 DOI: 10.3390/molecules28083304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
Glycosylation is a critical quality attribute in biotherapeutics, impacting properties such as protein stability, solubility, clearance rate, efficacy, immunogenicity, and safety. Due to the heterogenic and complex nature of protein glycosylation, comprehensive characterization is demanding. Moreover, the lack of standardized metrics for evaluating and comparing glycosylation profiles hinders comparability studies and the establishment of manufacturing control strategies. To address both challenges, we propose a standardized approach based on novel metrics for a comprehensive glycosylation fingerprint which greatly facilitates the reporting and objective comparison of glycosylation profiles. The analytical workflow is based on a liquid chromatography-mass spectrometry-based multi-attribute method. Based on the analytical data, a matrix of glycosylation-related quality attributes, both at site-specific and whole molecule level, are computed, which provide metrics for a comprehensive product glycosylation fingerprint. Two case studies illustrate the applicability of the proposed indices as a standardized and versatile approach for reporting all dimensions of the glycosylation profile. The proposed approach further facilitates the assessments of risks associated with changes in the glycosylation profile that may affect efficacy, clearance, and immunogenicity.
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Affiliation(s)
- Renato Mastrangeli
- Global CMC Development Technology & Innovation, CMC Science & Intelligence, Merck Serono SpA (An affiliate of Merck KGaA, Darmstadt, Germany), Guidonia Montecelio, 00012 Rome, Italy
| | - Abhijeet Satwekar
- Global CMC Development, Global Analytical Development, Global Analytical-Pharmaceutical Science & Innovation, Merck Serono SpA (An affiliate of Merck KGaA, Darmstadt, Germany), Guidonia Montecelio, 00012 Rome, Italy
| | - Horst Bierau
- Global CMC Development Technology & Innovation, CMC Science & Intelligence, Merck Serono SpA (An affiliate of Merck KGaA, Darmstadt, Germany), Guidonia Montecelio, 00012 Rome, Italy
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16
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Chau TH, Chernykh A, Kawahara R, Thaysen-Andersen M. Critical considerations in N-glycoproteomics. Curr Opin Chem Biol 2023; 73:102272. [PMID: 36758418 DOI: 10.1016/j.cbpa.2023.102272] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/30/2022] [Accepted: 01/05/2023] [Indexed: 02/10/2023]
Abstract
N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.
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Affiliation(s)
- The Huong Chau
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia
| | - Anastasia Chernykh
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia
| | - Rebeca Kawahara
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia
| | - Morten Thaysen-Andersen
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia; Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan.
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17
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Phetsanthad A, Vu NQ, Yu Q, Buchberger AR, Chen Z, Keller C, Li L. Recent advances in mass spectrometry analysis of neuropeptides. MASS SPECTROMETRY REVIEWS 2023; 42:706-750. [PMID: 34558119 PMCID: PMC9067165 DOI: 10.1002/mas.21734] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 08/22/2021] [Accepted: 08/28/2021] [Indexed: 05/08/2023]
Abstract
Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.
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Affiliation(s)
- Ashley Phetsanthad
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Nhu Q. Vu
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Qing Yu
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53705, USA
| | - Amanda R. Buchberger
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Zhengwei Chen
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Caitlin Keller
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53705, USA
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18
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McDowell CT, Lu X, Mehta AS, Angel PM, Drake RR. Applications and continued evolution of glycan imaging mass spectrometry. MASS SPECTROMETRY REVIEWS 2023; 42:674-705. [PMID: 34392557 PMCID: PMC8946722 DOI: 10.1002/mas.21725] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/16/2021] [Accepted: 08/03/2021] [Indexed: 05/03/2023]
Abstract
Glycosylation is an important posttranslational modifier of proteins and lipid conjugates critical for the stability and function of these macromolecules. Particularly important are N-linked glycans attached to asparagine residues in proteins. N-glycans have well-defined roles in protein folding, cellular trafficking and signal transduction, and alterations to them are implicated in a variety of diseases. However, the non-template driven biosynthesis of these N-glycans leads to significant structural diversity, making it challenging to identify the most biologically and clinically relevant species using conventional analyses. Advances in mass spectrometry instrumentation and data acquisition, as well as in enzymatic and chemical sample preparation strategies, have positioned mass spectrometry approaches as powerful analytical tools for the characterization of glycosylation in health and disease. Imaging mass spectrometry expands upon these strategies by capturing the spatial component of a glycan's distribution in-situ, lending additional insight into the organization and function of these molecules. Herein we review the ongoing evolution of glycan imaging mass spectrometry beginning with widely adopted tissue imaging approaches and expanding to other matrices and sample types with potential research and clinical implications. Adaptations of these techniques, along with their applications to various states of disease, are discussed. Collectively, glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.
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Affiliation(s)
- Colin T. McDowell
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Xiaowei Lu
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Anand S. Mehta
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Peggi M. Angel
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Richard R. Drake
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
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19
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Yin H, Zhu J. Methods for quantification of glycopeptides by liquid separation and mass spectrometry. MASS SPECTROMETRY REVIEWS 2023; 42:887-917. [PMID: 35099083 PMCID: PMC9339036 DOI: 10.1002/mas.21771] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 11/14/2021] [Accepted: 01/13/2022] [Indexed: 05/05/2023]
Abstract
Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.
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Affiliation(s)
- Haidi Yin
- Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518132, China
- Correspondence to: Haidi Yin, Shenzhen Bay Laboratory, A1201, Shenzhen, Guangdong, 518132, China. Phone: 0755-26849276. , Jianhui Zhu, Department of Surgery, University of Michigan, 1150 West Medical Center Drive, Building MSRB1, Rm A500, Ann Arbor, MI 48109-0656, USA. Tel: 734-615-2567. Fax: 734-615-2088.
| | - Jianhui Zhu
- Department of Surgery, University of Michigan, Ann Arbor, MI 48109, USA
- Correspondence to: Haidi Yin, Shenzhen Bay Laboratory, A1201, Shenzhen, Guangdong, 518132, China. Phone: 0755-26849276. , Jianhui Zhu, Department of Surgery, University of Michigan, 1150 West Medical Center Drive, Building MSRB1, Rm A500, Ann Arbor, MI 48109-0656, USA. Tel: 734-615-2567. Fax: 734-615-2088.
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20
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Polasky DA, Nesvizhskii AI. Recent advances in computational algorithms and software for large-scale glycoproteomics. Curr Opin Chem Biol 2023; 72:102238. [PMID: 36525809 DOI: 10.1016/j.cbpa.2022.102238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/12/2022] [Accepted: 11/14/2022] [Indexed: 12/15/2022]
Abstract
Glycoproteomics, or characterizing glycosylation events at a proteome scale, has seen rapid advances in methods for analyzing glycopeptides by tandem mass spectrometry in recent years. These advances have enabled acquisition of far more comprehensive and large-scale datasets, precipitating an urgent need for improved informatics methods to analyze the resulting data. A new generation of glycoproteomics search methods has recently emerged, using glycan fragmentation to split the identification of a glycopeptide into peptide and glycan components and solve each component separately. In this review, we discuss these new methods and their implications for large-scale glycoproteomics, as well as several outstanding challenges in glycoproteomics data analysis, including validation of glycan assignments and quantitation. Finally, we provide an outlook on the future of glycoproteomics from an informatics perspective, noting the key challenges to achieving widespread and reproducible glycopeptide annotation and quantitation.
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Affiliation(s)
- Daniel A Polasky
- University of Michigan Department of Pathology, Ann Arbor, MI, USA.
| | - Alexey I Nesvizhskii
- University of Michigan Department of Pathology, Ann Arbor, MI, USA; University of Michigan Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA.
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21
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Li M, Feng Y, Ma M, Kapur A, Patankar M, Li L. High-Throughput Quantitative Glycomics Enabled by 12-plex Isobaric Multiplex Labeling Reagents for Carbonyl-Containing Compound (SUGAR) Tags. J Proteome Res 2023; 22:1557-1563. [PMID: 36700627 PMCID: PMC10164053 DOI: 10.1021/acs.jproteome.2c00773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Glycans, which are widely distributed on most proteins and cell surfaces, are a class of important biomolecules playing crucial roles in various biological processes such as immune response and cellular communication. Modern mass spectrometry (MS) coupled with novel chemical probes greatly facilitates routine analysis of glycans. However, the requirement of high-throughput analysis still calls for advanced tools to be developed. Recently, we devised isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tags for 4-plex N-glycan analysis. To further improve the throughput, we utilized the subtle mass differences among different isotopologues and expanded the multiplexing capacity to 12 channels, a 3-fold throughput improvement for the original SUGAR tag design and achieved high-throughput N-glycan analysis in a single LC-MS/MS injection. We then applied 12-plex SUGAR tags to profile the N-glycans in four subtypes of human Immunoglobulin G (IgG) and to investigate the N-glycan changes in the endometrial cancer cells (ECC1) treated with Atovaquone, a quinone antimicrobial medication, and a dihydroorotate dehydrogenase (DHODH) inhibitor. Data are available via ProteomeXchange with the identifier PXD038501.
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22
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Delafield DG, Miles HN, Ricke WA, Li L. Higher Temperature Porous Graphitic Carbon Separations Differentially Impact Distinct Glycopeptide Classes. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:64-74. [PMID: 36450095 PMCID: PMC9812930 DOI: 10.1021/jasms.2c00249] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Mass spectrometry-based discovery glycoproteomics is highly dependent on the use of chromatography paradigms amenable to analyte retention and separation. When compared against established stationary phases such as reversed-phase and hydrophilic interaction liquid chromatography, reports utilizing porous graphitic carbon have detailed its numerous advantages. Recent efforts have highlighted the utility in porous graphitic carbon in high-throughput glycoproteomics, principally through enhanced profiling depth and liquid-phase resolution at higher column temperatures. However, increasing column temperature has been shown to impart disparaging effects in glycopeptide identification. Herein we further elucidate this trend, describing qualitative and semiquantitative effects of increased column temperature on glycopeptide identification rates, signal intensity, resolution, and spectral count linear response. Through analysis of enriched bovine and human glycopeptides, species with high mannose and sialylated glycans were shown to most significantly benefit and suffer from high column temperatures, respectively. These results provide insight as to how porous graphitic carbon separations may be appropriately leveraged for glycopeptide identification while raising concerns over quantitative and semiquantitative label-free comparisons as the temperature changes. RAW MS glycoproteomic data are available via ProteomeXchange with identifier PXD034354.
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Affiliation(s)
- Daniel G. Delafield
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706
| | - Hannah N. Miles
- Division of Pharmaceutical Sciences, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53075
| | - William A. Ricke
- Division of Pharmaceutical Sciences, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53075
- George M. O’Brien Urology Research Center of Excellence, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
- Department of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706
- Division of Pharmaceutical Sciences, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53075
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23
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Firdous P, Hassan T, Farooq S, Nissar K. Applications of proteomics in cancer diagnosis. Proteomics 2023. [DOI: 10.1016/b978-0-323-95072-5.00014-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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24
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Doud EH, Yeh ES. Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery. Technol Cancer Res Treat 2023; 22:15330338221148811. [PMID: 36740994 PMCID: PMC9903044 DOI: 10.1177/15330338221148811] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.
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Affiliation(s)
- Emma H. Doud
- Center for Proteome Analysis, Indiana University School of Medicine, Indianapolis, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, USA
- IU Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, USA
| | - Elizabeth S. Yeh
- IU Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, USA
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25
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pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 2022; 13:7539. [PMID: 36477196 PMCID: PMC9729625 DOI: 10.1038/s41467-022-35172-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
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.
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26
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Lageveen‐Kammeijer GSM, Kuster B, Reusch D, Wuhrer M. High sensitivity glycomics in biomedicine. MASS SPECTROMETRY REVIEWS 2022; 41:1014-1039. [PMID: 34494287 PMCID: PMC9788051 DOI: 10.1002/mas.21730] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 08/23/2021] [Accepted: 08/26/2021] [Indexed: 05/15/2023]
Abstract
Many analytical challenges in biomedicine arise from the generally high heterogeneity and complexity of glycan- and glycoconjugate-containing samples, which are often only available in minute amounts. Therefore, highly sensitive workflows and detection methods are required. In this review mass spectrometric workflows and detection methods are evaluated for glycans and glycoproteins. Furthermore, glycomic methodologies and innovations that are tailored for enzymatic treatments, chemical derivatization, purification, separation, and detection at high sensitivity are highlighted. The discussion is focused on the analysis of mammalian N-linked and GalNAc-type O-linked glycans.
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Affiliation(s)
| | - Bernhard Kuster
- Chair for Proteomics and BioanalyticsTechnical University of MunichFreisingGermany
| | - Dietmar Reusch
- Pharma Technical Development EuropeRoche Diagnostics GmbHPenzbergGermany
| | - Manfred Wuhrer
- Leiden University Medical CenterCenter for Proteomics and MetabolomicsLeidenThe Netherlands
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27
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Chang D, Zaia J. Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data. MASS SPECTROMETRY REVIEWS 2022; 41:922-937. [PMID: 33764573 DOI: 10.1002/mas.21692] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/24/2020] [Accepted: 03/11/2021] [Indexed: 05/18/2023]
Abstract
Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.
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Affiliation(s)
- Deborah Chang
- Department of Biochemistry, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Joseph Zaia
- Department of Biochemistry, Boston University School of Medicine, Boston, Massachusetts, USA
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28
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Trbojević-Akmačić I, Lageveen-Kammeijer GSM, Heijs B, Petrović T, Deriš H, Wuhrer M, Lauc G. High-Throughput Glycomic Methods. Chem Rev 2022; 122:15865-15913. [PMID: 35797639 PMCID: PMC9614987 DOI: 10.1021/acs.chemrev.1c01031] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.
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Affiliation(s)
| | | | - Bram Heijs
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Tea Petrović
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Helena Deriš
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Manfred Wuhrer
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Gordan Lauc
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
- Faculty
of Pharmacy and Biochemistry, University
of Zagreb, A. Kovačića 1, 10 000 Zagreb, Croatia
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29
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Guan B, Zhang Z, Chai Y, Amantai X, Chen X, Cao X, Yue X. N-glycosylation of milk proteins: A review spanning 2010–2022. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2022.07.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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30
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Liu Y, Wu F, Wang J, Pu L, Ding CF. Simultaneous chirality separation of amino acids and their derivative by natamycin based on mobility measurements. Anal Chim Acta 2022; 1227:340298. [DOI: 10.1016/j.aca.2022.340298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 11/01/2022]
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31
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Sorieul C, Papi F, Carboni F, Pecetta S, Phogat S, Adamo R. Recent advances and future perspectives on carbohydrate-based cancer vaccines and therapeutics. Pharmacol Ther 2022; 235:108158. [PMID: 35183590 DOI: 10.1016/j.pharmthera.2022.108158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 01/30/2022] [Accepted: 02/14/2022] [Indexed: 12/13/2022]
Abstract
Carbohydrates are abundantly expressed on the surface of both eukaryotic and prokaryotic cells, often as post translational modifications of proteins. Glycoproteins are recognized by the immune system and can trigger both innate and humoral responses. This feature has been harnessed to generate vaccines against polysaccharide-encapsulated bacteria such as Streptococcus pneumoniae, Hemophilus influenzae type b and Neisseria meningitidis. In cancer, glycosylation plays a pivotal role in malignancy development and progression. Since glycans are specifically expressed on the surface of tumor cells, they have been targeted for the discovery of anticancer preventive and therapeutic treatments, such as vaccines and monoclonal antibodies. Despite the various efforts made over the last years, resulting in a series of clinical studies, attempts of vaccination with carbohydrate-based candidates have proven unsuccessful, primarily due to the immune tolerance often associated with these glycans. New strategies are thus deployed to enhance carbohydrate-based cancer vaccines. Moreover, lessons learned from glycan immunobiology paved the way to the development of new monoclonal antibodies specifically designed to recognize cancer-bound carbohydrates and induce tumor cell killing. Herein we provide an overview of the immunological principles behind the immune response towards glycans and glycoconjugates and the approaches exploited at both preclinical and clinical level to target cancer-associated glycans for the development of vaccines and therapeutic monoclonal antibodies. We also discuss gaps and opportunities to successfully advance glycan-directed cancer therapies, which could provide patients with innovative and effective treatments.
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32
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Ince D, Lucas TM, Malaker SA. Current strategies for characterization of mucin-domain glycoproteins. Curr Opin Chem Biol 2022; 69:102174. [PMID: 35752002 DOI: 10.1016/j.cbpa.2022.102174] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/02/2022] [Accepted: 05/19/2022] [Indexed: 11/18/2022]
Abstract
Glycosylation, and especially O-linked glycosylation, remains a critical blind spot in the understanding of post-translational modifications. Due to their nature as proteins defined by a large density and abundance of O-glycosylation, mucins present extra challenges in the analysis of their structure and function. However, recent breakthroughs in multiple areas of research have rendered mucin-domain glycoproteins more accessible to current characterization techniques. In particular, the adaptation of mucinases to glycoproteomic workflows, the manipulation of cellular glycosylation pathways, and the advances in synthetic methods to more closely mimic mucin domains have introduced new and exciting avenues to study mucin glycoproteins. Here, we summarize recent developments in understanding the structure and biological function of mucin domains and their associated glycans, from glycoproteomic tools and visualization methods to synthetic glycopeptide mimetics.
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Affiliation(s)
- Deniz Ince
- Department of Chemistry, Yale University, 275 Prospect St, New Haven, CT 06511, United States
| | - Taryn M Lucas
- Department of Chemistry, Yale University, 275 Prospect St, New Haven, CT 06511, United States
| | - Stacy A Malaker
- Department of Chemistry, Yale University, 275 Prospect St, New Haven, CT 06511, United States.
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33
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Xie X, Li J, Zhen X, Chen L, Yuan W, Feng Q, Liu X. Rational construction of fluorescent molecular imprinted polymers for highly efficient glycoprotein detection. Anal Chim Acta 2022; 1209:339875. [DOI: 10.1016/j.aca.2022.339875] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 04/11/2022] [Accepted: 04/22/2022] [Indexed: 11/01/2022]
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34
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Wilson J, Bilbao A, Wang J, Liao YC, Velickovic D, Wojcik R, Passamonti M, Zhao R, Gargano AFG, Gerbasi VR, Pas̆a-Tolić L, Baker SE, Zhou M. Online Hydrophilic Interaction Chromatography (HILIC) Enhanced Top-Down Mass Spectrometry Characterization of the SARS-CoV-2 Spike Receptor-Binding Domain. Anal Chem 2022; 94:5909-5917. [PMID: 35380435 PMCID: PMC9003935 DOI: 10.1021/acs.analchem.2c00139] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/25/2022] [Indexed: 12/13/2022]
Abstract
SARS-CoV-2 cellular infection is mediated by the heavily glycosylated spike protein. Recombinant versions of the spike protein and the receptor-binding domain (RBD) are necessary for seropositivity assays and can potentially serve as vaccines against viral infection. RBD plays key roles in the spike protein's structure and function, and thus, comprehensive characterization of recombinant RBD is critically important for biopharmaceutical applications. Liquid chromatography coupled to mass spectrometry has been widely used to characterize post-translational modifications in proteins, including glycosylation. Most studies of RBDs were performed at the proteolytic peptide (bottom-up proteomics) or released glycan level because of the technical challenges in resolving highly heterogeneous glycans at the intact protein level. Herein, we evaluated several online separation techniques: (1) C2 reverse-phase liquid chromatography (RPLC), (2) capillary zone electrophoresis (CZE), and (3) acrylamide-based monolithic hydrophilic interaction chromatography (HILIC) to separate intact recombinant RBDs with varying combinations of glycosylations (glycoforms) for top-down mass spectrometry (MS). Within the conditions we explored, the HILIC method was superior to RPLC and CZE at separating RBD glycoforms, which differ significantly in neutral glycan groups. In addition, our top-down analysis readily captured unexpected modifications (e.g., cysteinylation and N-terminal sequence variation) and low abundance, heavily glycosylated proteoforms that may be missed by using glycopeptide data alone. The HILIC top-down MS platform holds great potential in resolving heterogeneous glycoproteins for facile comparison of biosimilars in quality control applications.
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Affiliation(s)
- Jesse
W. Wilson
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Aivett Bilbao
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Juan Wang
- Biological
Sciences Division, Pacific Northwest National
Laboratories, 902 Battelle
Boulevard, Richland, Washington 99354, United States
| | - Yen-Chen Liao
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Dusan Velickovic
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Roza Wojcik
- National
Security Directorate, Pacific Northwest
National Laboratories, 902 Battelle Boulevard, Richland, Washington 99354, United States
| | - Marta Passamonti
- Centre
for Analytical Sciences Amsterdam, Amsterdam 1098 XH, The
Netherlands
- Van’t
Hoff Institute for Molecular Sciences, University
of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Rui Zhao
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Andrea F. G. Gargano
- Centre
for Analytical Sciences Amsterdam, Amsterdam 1098 XH, The
Netherlands
- Van’t
Hoff Institute for Molecular Sciences, University
of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Vincent R. Gerbasi
- Biological
Sciences Division, Pacific Northwest National
Laboratories, 902 Battelle
Boulevard, Richland, Washington 99354, United States
| | - Ljiljana Pas̆a-Tolić
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Scott E. Baker
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
| | - Mowei Zhou
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, 3335 Innovation Boulevard, Richland, Washington 99354, United States
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35
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Escobar EE, Wang S, Goswami R, Lanzillotti MB, Li L, McLellan JS, Brodbelt JS. Analysis of Viral Spike Protein N-Glycosylation Using Ultraviolet Photodissociation Mass Spectrometry. Anal Chem 2022; 94:5776-5784. [PMID: 35388686 PMCID: PMC9272412 DOI: 10.1021/acs.analchem.1c04874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Characterization of protein glycosylation by tandem mass spectrometry remains challenging owing to the vast diversity of oligosaccharides bound to proteins, the variation in monosaccharide linkage patterns, and the lability of the linkage between the glycan and protein. Here, we have adapted an HCD-triggered-ultraviolet photodissociation (UVPD) approach for the simultaneous localization of glycosites and full characterization of both glycan compositions and intersaccharide linkages, the latter provided by extensive cross-ring cleavages enabled by UVPD. The method is applied to study glycan compositions based on analysis of glycopeptides from proteolytic digestion of recombinant human coronaviruse spike proteins from SARS-CoV-2 and HKU1. UVPD reveals unique intersaccharide linkage information and is leveraged to localize N-linked glycoforms with confidence.
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Affiliation(s)
- Edwin E Escobar
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Shuaishuai Wang
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, United States
| | | | - Michael B Lanzillotti
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Lei Li
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Jason S McLellan
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Jennifer S Brodbelt
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
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36
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García-Artalejo JA, Mancera-Arteu M, Sanz-Nebot V, Rodríguez T, Giménez E. CHARACTERIZING A NOVEL HYPOSIALYLATED ERYTHROPOIETIN BY INTACT GLYCOPROTEIN AND GLYCAN ANALYSIS. J Pharm Biomed Anal 2022; 213:114686. [DOI: 10.1016/j.jpba.2022.114686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 02/09/2022] [Accepted: 02/20/2022] [Indexed: 10/19/2022]
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37
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On-tissue amidation of sialic acid with aniline for sensitive imaging of sialylated N-glycans from FFPE tissue sections via MALDI mass spectrometry. Anal Bioanal Chem 2022; 414:5263-5274. [DOI: 10.1007/s00216-022-03894-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 12/24/2021] [Accepted: 01/10/2022] [Indexed: 01/06/2023]
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38
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The simultaneous profiling of 14 free monosaccharides in biofluids by a LC-MS/MS method. J Chromatogr B Analyt Technol Biomed Life Sci 2022; 1192:123086. [DOI: 10.1016/j.jchromb.2021.123086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 12/07/2021] [Accepted: 12/13/2021] [Indexed: 11/23/2022]
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39
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Zhang Y, Zheng S, Mao Y, Cao W, Zhao L, Wu C, Cheng J, Liu F, Li G, Yang H. Systems analysis of plasma IgG intact N-glycopeptides from patients with chronic kidney diseases via EThcD-sceHCD-MS/MS. Analyst 2021; 146:7274-7283. [PMID: 34747425 DOI: 10.1039/d1an01657a] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Immunoglobulin G (IgG) molecules modulate an immune response. However, site-specific N-glycosylation signatures of plasma IgG in patients with chronic kidney disease (CKD) remain unclear. This study aimed to propose a novel method to explore the N-glycosylation pattern of IgG and to compare it with reported methods. We separated human plasma IgG from 58 healthy controls (HC) and 111 patients with CKD. Purified IgG molecules were digested by trypsin. Tryptic peptides without enrichment of intact N-glycopeptides were analyzed using a combination of electron-transfer/higher-energy collisional dissociation (EThcD) and stepped collision energy/higher-energy collisional dissociation (sceHCD) mass spectrometry (EThcD-sceHCD-MS/MS). This resulted in higher spectral quality, more informative fragment ions, higher Byonic score, and nearly twice the depth of intact N-glycopeptide identification than sceHCD or EThcD alone. Site-specific N-glycosylation mapping revealed that intact N-glycopeptides were differentially expressed in HC and CKD patients; thus, it can be a diagnostic tool. This study provides a method for the determination of glycosylation patterns in CKD and a framework for understanding the role of IgG in the pathophysiology of CKD. Data are available via ProteomeXchange with identifier PXD027174.
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Affiliation(s)
- Yong Zhang
- NHC Key Laboratory of Transplant Engineering and Immunology, Institutes for Systems Genetics; National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China. .,Sichuan Provincial Engineering Laboratory of Pathology in Clinical Application, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Shanshan Zheng
- NHC Key Laboratory of Transplant Engineering and Immunology, Institutes for Systems Genetics; National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Yonghong Mao
- Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Wei Cao
- NHC Key Laboratory of Transplant Engineering and Immunology, Institutes for Systems Genetics; National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Lijun Zhao
- Division of Nephrology, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Changwei Wu
- Renal Department and Institute of Nephrology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu 611731, China.
| | - Jingqiu Cheng
- NHC Key Laboratory of Transplant Engineering and Immunology, Institutes for Systems Genetics; National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Fang Liu
- Division of Nephrology, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Guisen Li
- Renal Department and Institute of Nephrology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu 611731, China.
| | - Hao Yang
- NHC Key Laboratory of Transplant Engineering and Immunology, Institutes for Systems Genetics; National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China. .,Sichuan Provincial Engineering Laboratory of Pathology in Clinical Application, West China Hospital, Sichuan University, Chengdu 610041, China
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40
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Kim J, Yin D, Lee J, An HJ, Kim TY. Deuterium Oxide Labeling for Global Omics Relative Quantification (DOLGOReQ): Application to Glycomics. Anal Chem 2021; 93:14497-14505. [PMID: 34724788 DOI: 10.1021/acs.analchem.1c03157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A new relative quantification strategy for glycomics, named deuterium oxide (D2O) labeling for global omics relative quantification (DOLGOReQ), has been developed based on the partial metabolic D2O labeling, which induces a subtle change in the isotopic distribution of glycan ions. The relative abundance of unlabeled to D-labeled glycans was extracted from the overlapped isotopic envelope obtained from a mixture containing equal amounts of unlabeled and D-labeled glycans. The glycan quantification accuracy of DOLGOReQ was examined with mixtures of unlabeled and D-labeled HeLa glycans combined in varying ratios according to the number of cells present in the samples. The relative quantification of the glycans mixed in an equimolar ratio revealed that 92.4 and 97.8% of the DOLGOReQ results were within a 1.5- and 2-fold range of the predicted mixing ratio, respectively. Furthermore, the dynamic quantification range of DOLGOReQ was investigated with unlabeled and D-labeled HeLa glycans mixed in different ratios from 20:1 to 1:20. A good correlation (Pearson's r > 0.90) between the expected and measured quantification ratios over 2 orders of magnitude was observed for 87% of the quantified glycans. DOLGOReQ was also applied in the measurement of quantitative HeLa cell glycan changes that occur under normoxic and hypoxic conditions. Given that metabolic D2O labeling can incorporate D into all types of glycans, DOLGOReQ has the potential as a universal quantification platform for large-scale comparative glycomic experiments.
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Affiliation(s)
- Jonghyun Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju 61005, South Korea
| | - Dongtan Yin
- Asia-Pacific Glycomics Reference Site, Chungnam National University, Daejeon 34134, South Korea.,Graduate School of Analytical & Science Technology, Chungnam National University, Daejeon 34134, South Korea
| | - Jua Lee
- Asia-Pacific Glycomics Reference Site, Chungnam National University, Daejeon 34134, South Korea.,Graduate School of Analytical & Science Technology, Chungnam National University, Daejeon 34134, South Korea
| | - Hyun Joo An
- Asia-Pacific Glycomics Reference Site, Chungnam National University, Daejeon 34134, South Korea.,Graduate School of Analytical & Science Technology, Chungnam National University, Daejeon 34134, South Korea
| | - Tae-Young Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju 61005, South Korea
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41
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Gutierrez-Reyes CD, Jiang P, Atashi M, Bennett A, Yu A, Peng W, Zhong J, Mechref Y. Advances in mass spectrometry-based glycoproteomics: An update covering the period 2017-2021. Electrophoresis 2021; 43:370-387. [PMID: 34614238 DOI: 10.1002/elps.202100188] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/30/2021] [Accepted: 09/25/2021] [Indexed: 12/23/2022]
Abstract
Protein glycosylation is one of the most common posttranslational modifications, and plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, host-pathogen interaction, and protein stability. Glycoproteomics is a proteomics subfield dedicated to identifying and characterizing the glycans and glycoproteins in a given cell or tissue. Aberrant glycosylation has been associated with various diseases such as Alzheimer's disease, viral infections, inflammation, immune deficiencies, congenital disorders, and cancers. However, glycoproteomic analysis remains challenging because of the low abundance, site-specific heterogeneity, and poor ionization efficiency of glycopeptides during LC-MS analyses. Therefore, the development of sensitive and accurate approaches to efficiently characterize protein glycosylation is crucial. Methods such as metabolic labeling, enrichment, and derivatization of glycopeptides, coupled with different mass spectrometry techniques and bioinformatics tools, have been developed to achieve sophisticated levels of quantitative and qualitative analyses of glycoproteins. This review attempts to update the recent developments in the field of glycoproteomics reported between 2017 and 2021.
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Affiliation(s)
| | - Peilin Jiang
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Mojgan Atashi
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Andrew Bennett
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Aiying Yu
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Wenjing Peng
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Jieqiang Zhong
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Yehia Mechref
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
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42
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Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence. Biochem Soc Trans 2021; 49:1905-1926. [PMID: 34374408 DOI: 10.1042/bst20191088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 07/19/2021] [Accepted: 07/21/2021] [Indexed: 11/17/2022]
Abstract
Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.
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43
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Miles HN, Delafield DG, Li L. Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research. RSC Chem Biol 2021; 4:1050-1072. [PMID: 34430874 PMCID: PMC8341969 DOI: 10.1039/d1cb00039j] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/18/2021] [Indexed: 12/28/2022] Open
Abstract
Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.
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Affiliation(s)
- Hannah N. Miles
- School of Pharmacy, University of Wisconsin-Madison777 Highland AvenueMadisonWI53705-2222USA+1-608-262-5345+1-608-265-8491
| | | | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison777 Highland AvenueMadisonWI53705-2222USA+1-608-262-5345+1-608-265-8491
- Department of Chemistry, University of Wisconsin-MadisonMadisonWI53706USA
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44
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Tabang DN, Ford M, Li L. Recent Advances in Mass Spectrometry-Based Glycomic and Glycoproteomic Studies of Pancreatic Diseases. Front Chem 2021; 9:707387. [PMID: 34368082 PMCID: PMC8342852 DOI: 10.3389/fchem.2021.707387] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 07/12/2021] [Indexed: 12/14/2022] Open
Abstract
Modification of proteins by glycans plays a crucial role in mediating biological functions in both healthy and diseased states. Mass spectrometry (MS) has emerged as the most powerful tool for glycomic and glycoproteomic analyses advancing knowledge of many diseases. Such diseases include those of the pancreas which affect millions of people each year. In this review, recent advances in pancreatic disease research facilitated by MS-based glycomic and glycoproteomic studies will be examined with a focus on diabetes and pancreatic cancer. The last decade, and especially the last five years, has witnessed developments in both discovering new glycan or glycoprotein biomarkers and analyzing the links between glycans and disease pathology through MS-based studies. The strength of MS lies in the specificity and sensitivity of liquid chromatography-electrospray ionization MS for measuring a wide range of biomolecules from limited sample amounts from many sample types, greatly enhancing and accelerating the biomarker discovery process. Furthermore, imaging MS of glycans enabled by matrix-assisted laser desorption/ionization has proven useful in complementing histology and immunohistochemistry to monitor pancreatic disease progression. Advances in biological understanding and analytical techniques, as well as challenges and future directions for the field, will be discussed.
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Affiliation(s)
- Dylan Nicholas Tabang
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, United States
| | - Megan Ford
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, United States
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, United States.,School of Pharmacy, University of Wisconsin-Madison, Madison, WI, United States
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45
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Shu H, Zhang L, Chen Y, Guo Y, Li L, Chen F, Cao Z, Yan G, Lu C, Liu C, Zhang S. Quantification of Intact O-Glycopeptides on Haptoglobin in Sera of Patients With Hepatocellular Carcinoma and Liver Cirrhosis. Front Chem 2021; 9:705341. [PMID: 34336790 PMCID: PMC8316590 DOI: 10.3389/fchem.2021.705341] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 06/16/2021] [Indexed: 12/02/2022] Open
Abstract
Haptoglobin (Hp) is one of the acute-phase response proteins secreted by the liver, and its aberrant N-glycosylation was previously reported in hepatocellular carcinoma (HCC). Limited studies on Hp O-glycosylation have been previously reported. In this study, we aimed to discover and confirm its O-glycosylation in HCC based on lectin binding and mass spectrometry (MS) detection. First, serum Hp was purified from patients with liver cirrhosis (LC) and HCC, respectively. Then, five lectins with Gal or GalNAc monosaccharide specificity were chosen to perform lectin blot, and the results showed that Hp in HCC bound to these lectins in a much stronger manner than that in LC. Furthermore, label-free quantification based on MS was performed. A total of 26 intact O-glycopeptides were identified on Hp, and most of them were elevated in HCC as compared to LC. Among them, the intensity of HYEGS316TVPEK (H1N1S1) on Hp was the highest in HCC patients. Increased HYEGS316TVPEK (H1N1S1) in HCC was quantified and confirmed using the MS method based on 18O/16O C-terminal labeling and multiple reaction monitoring. This study provided a comprehensive understanding of the glycosylation of Hp in liver diseases.
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Affiliation(s)
- Hong Shu
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China.,Department of Clinical Laboratory, Cancer Hospital of Guangxi Medical University, Nanning, China
| | - Lei Zhang
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Yiwei Chen
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yijie Guo
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Limin Li
- Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Fanghua Chen
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Zhao Cao
- Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Guoquan Yan
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Chunlai Lu
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chao Liu
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Shu Zhang
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
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46
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Sauer CS, Phetsanthad A, Riusech OL, Li L. Developing mass spectrometry for the quantitative analysis of neuropeptides. Expert Rev Proteomics 2021; 18:607-621. [PMID: 34375152 PMCID: PMC8522511 DOI: 10.1080/14789450.2021.1967146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/09/2021] [Indexed: 12/22/2022]
Abstract
INTRODUCTION Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function. AREAS COVERED We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements. EXPERT OPINION Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.
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Affiliation(s)
- Christopher S. Sauer
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Ashley Phetsanthad
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Olga L. Riusech
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53075, USA
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47
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Hart GW, Wells L. Glycoproteomics: Making the Study of the Most Structurally Diverse and Most Abundant Post-Translational Modifications More Accessible to the Scientific Community. Mol Cell Proteomics 2021; 20:100086. [PMID: 34091217 PMCID: PMC8724864 DOI: 10.1016/j.mcpro.2021.100086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- Gerald W Hart
- Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia, USA
| | - Lance Wells
- Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia, USA
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48
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Wang S, Liu D, Qu J, Zhu H, Chen C, Gibbons C, Greenway H, Wang P, Bollag RJ, Liu K, Li L. Streamlined Subclass-Specific Absolute Quantification of Serum IgG Glycopeptides Using Synthetic Isotope-Labeled Standards. Anal Chem 2021; 93:4449-4455. [PMID: 33630567 PMCID: PMC8715724 DOI: 10.1021/acs.analchem.0c04462] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Absolute glycoproteomics quantification has drawn tremendous attention owing to its prospects in biomarker discovery and clinical implementation but is impeded by a general lack of suitable heavy isotope-labeled glycopeptide standards. In this study, we devised a facile chemoenzymatic strategy to synthesize a total of 36 human IgG glycopeptides attached with well-defined glycoforms, including 15 isotope-labeled ones with a mass increment of 6 Da to their native counterparts. Spiking of these standards into human sera enabled simplified, robust, and precise absolute quantification of IgG glycopeptides in a subclass-specific fashion. Additionally, the implementation of the absolute quantification approach revealed subclass-dependent alteration of serum IgG galactosylation and sialylation in colon cancer samples.
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Affiliation(s)
- Shuaishuai Wang
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Ding Liu
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Jingyao Qu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, Shandong, China
| | - He Zhu
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Congcong Chen
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Christopher Gibbons
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Harmon Greenway
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Peng Wang
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Roni J Bollag
- Department of Pathology, Augusta University, Augusta, Georgia 30912, United States
| | - Kebin Liu
- Department of Biochemistry and Molecular Biology, Augusta University, Augusta, Georgia 30912, United States
| | - Lei Li
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
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49
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Ma J, Wu C, Hart GW. Analytical and Biochemical Perspectives of Protein O-GlcNAcylation. Chem Rev 2021; 121:1513-1581. [DOI: 10.1021/acs.chemrev.0c00884] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Junfeng Ma
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Georgetown University, Washington D.C. 20057, United States
| | - Ci Wu
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Georgetown University, Washington D.C. 20057, United States
| | - Gerald W. Hart
- Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602, United States
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50
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Hackett WE, Zaia J. Calculating Glycoprotein Similarities From Mass Spectrometric Data. Mol Cell Proteomics 2021; 20:100028. [PMID: 32883803 PMCID: PMC8724611 DOI: 10.1074/mcp.r120.002223] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 08/24/2020] [Accepted: 09/03/2020] [Indexed: 12/23/2022] Open
Abstract
Complex protein glycosylation occurs through biosynthetic steps in the secretory pathway that create macro- and microheterogeneity of structure and function. Required for all life forms, glycosylation diversifies and adapts protein interactions with binding partners that underpin interactions at cell surfaces and pericellular and extracellular environments. Because these biological effects arise from heterogeneity of structure and function, it is necessary to measure their changes as part of the quest to understand nature. Quite often, however, the assumption behind proteomics that posttranslational modifications are discrete additions that can be modeled using the genome as a template does not apply to protein glycosylation. Rather, it is necessary to quantify the glycosylation distribution at each glycosite and to aggregate this information into a population of mature glycoproteins that exist in a given biological system. To date, mass spectrometric methods for assigning singly glycosylated peptides are well-established. But it is necessary to quantify glycosylation heterogeneity accurately in order to gauge the alterations that occur during biological processes. The task is to quantify the glycosylated peptide forms as accurately as possible and then apply appropriate bioinformatics algorithms to the calculation of micro- and macro-similarities. In this review, we summarize current approaches for protein quantification as they apply to this glycoprotein similarity problem.
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Affiliation(s)
- William E Hackett
- Bioinformatics Program, Boston University, Boston, Massachusetts, USA
| | - Joseph Zaia
- Bioinformatics Program, Boston University, Boston, Massachusetts, USA; Department of Biochemistry, Boston University, Boston, Massachusetts, USA.
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