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Dalal KB, Yang W, Tian E, Chernish A, McCluggage P, Lara AJ, Ten Hagen KG, Tabak LA. In vivo Mapping of the Mouse Galnt3-specific O-Glycoproteome. J Biol Chem 2024:107628. [PMID: 39098533 DOI: 10.1016/j.jbc.2024.107628] [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: 01/22/2024] [Revised: 07/23/2024] [Accepted: 07/24/2024] [Indexed: 08/06/2024] Open
Abstract
The UDP-N-acetylgalactosamine polypeptide:N-acetylgalactosaminyltransferase (GalNAc-T) family of enzymes initiates O-linked glycosylation by catalyzing the addition of the first GalNAc sugar to serine or threonine on proteins destined to be membrane-bound or secreted. Defects in individual isoforms of the GalNAc-T family can lead to certain congenital disorders of glycosylation (CDG). The GALNT3-CDG, is caused by mutations in GALNT3, resulting in hyperphosphatemic familial tumoral calcinosis (HFTC) due to impaired glycosylation of the phosphate-regulating hormone FGF23 within osteocytes of the bone. Patients with hyperphosphatemia present altered bone density, abnormal tooth structure and calcified masses throughout the body. It is therefore important to identify all potential substrates of GalNAc-T3 throughout the body to understand the complex disease phenotypes. Here, we compared the Galnt3-/- mouse model, which partially phenocopies GALNT3-CDG, with wild-type mice and employed a multi-component approach utilizing chemoenzymatic conditions, a product-dependent method constructed using EThcD triggered scans in a mass spectrometry workflow, quantitative O-glycoproteomics, and global proteomics to identify 663 Galnt3-specific O-glycosites from 269 glycoproteins across multiple tissues. Consistent with the mouse and human phenotypes, functional networks of glycoproteins that contain GalNAc-T3-specific O-glycosites involved in skeletal morphology, mineral level maintenance and hemostasis were identified. This library of in vivo GalNAc-T3-specific substrate proteins and O-glycosites will serve as a valuable resource to understand the functional implications of O-glycosylation and to unravel the underlying causes of complex human GALNT3-CDG phenotypes.
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Affiliation(s)
- Kruti Bhavik Dalal
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Weiming Yang
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - E Tian
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Aliona Chernish
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Peggy McCluggage
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Alexander J Lara
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Kelly G Ten Hagen
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Lawrence A Tabak
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892.
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2
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Budhraja R, Joshi N, Radenkovic S, Kozicz T, Morava E, Pandey A. Dysregulated proteome and N-glycoproteome in ALG1-deficient fibroblasts. Proteomics 2024; 24:e2400012. [PMID: 38470198 PMCID: PMC7616334 DOI: 10.1002/pmic.202400012] [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: 01/08/2024] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/13/2024]
Abstract
Asparagine-linked glycosylation 1 protein is a β-1,4-mannosyltransferase, is encoded by the ALG1 gene, which catalyzes the first step of mannosylation in N-glycosylation. Pathogenic variants in ALG1 cause a rare autosomal recessive disorder termed as ALG1-CDG. We performed a quantitative proteomics and N-glycoproteomics study in fibroblasts derived from patients with one homozygous and two compound heterozygous pathogenic variants in ALG1. Several proteins that exhibited significant upregulation included insulin-like growth factor II and pleckstrin, whereas hyaluronan and proteoglycan link protein 1 was downregulated. These proteins are crucial for cell growth, survival and differentiation. Additionally, we observed a decrease in the expression of mitochondrial proteins and an increase in autophagy-related proteins, suggesting mitochondrial and cellular stress. N-glycoproteomics revealed the reduction in high-mannose and complex/hybrid glycopeptides derived from numerous proteins in patients explaining that defect in ALG1 has broad effects on glycosylation. Further, we detected an increase in several short oligosaccharides, including chitobiose (HexNAc2) trisaccharides (Hex-HexNAc2) and novel tetrasaccharides (NeuAc-Hex-HexNAc2) derived from essential proteins including LAMP1, CD44 and integrin. These changes in glycosylation were observed in all patients irrespective of their gene variants. Overall, our findings not only provide novel molecular insights into understanding ALG1-CDG but also offer short oligosaccharide-bearing peptides as potential biomarkers.
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Affiliation(s)
- Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Neha Joshi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Silvia Radenkovic
- Department of Clinical Genomics, Mayo Clinic, Rochester, Minnesota, USA
| | - Tamas Kozicz
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Clinical Genomics, Mayo Clinic, Rochester, Minnesota, USA
| | - Eva Morava
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Clinical Genomics, Mayo Clinic, Rochester, Minnesota, USA
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Manipal Academy of Higher Education, Manipal, Karnataka, India
- Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
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3
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Klein J, Carvalho L, Zaia J. Expanding N-glycopeptide identifications by modeling fragmentation, elution, and glycome connectivity. Nat Commun 2024; 15:6168. [PMID: 39039063 PMCID: PMC11263600 DOI: 10.1038/s41467-024-50338-5] [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: 01/26/2021] [Accepted: 07/08/2024] [Indexed: 07/24/2024] Open
Abstract
Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft .
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Affiliation(s)
- Joshua Klein
- Program for Bioinformatics, Boston University, Boston, MA, US.
| | - Luis Carvalho
- Program for Bioinformatics, Boston University, Boston, MA, US
- Department of Math and Statistics, Boston University, Boston, MA, US
| | - Joseph Zaia
- Program for Bioinformatics, Boston University, Boston, MA, US.
- Department of Biochemistry and Cell Biology, Boston University, Boston, MA, US.
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4
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DeBono NJ, Moh ESX, Packer NH. Experimentally Determined Diagnostic Ions for Identification of Peptide Glycotopes. J Proteome Res 2024; 23:2661-2673. [PMID: 38888225 DOI: 10.1021/acs.jproteome.3c00858] [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: 06/20/2024]
Abstract
The analysis of the structures of glycans present on glycoproteins is an essential component for determining glycoprotein function; however, detailed glycan structural assignment on glycopeptides from proteomics mass spectrometric data remains challenging. Glycoproteomic analysis by mass spectrometry currently can provide significant, yet incomplete, information about the glycans present, including the glycan monosaccharide composition and in some circumstances the site(s) of glycosylation. Advancements in mass spectrometric resolution, using high-mass accuracy instrumentation and tailored MS/MS fragmentation parameters, coupled with a dedicated definition of diagnostic fragmentation ions have enabled the determination of some glycan structural features, or glycotopes, expressed on glycopeptides. Here we present a collation of diagnostic glycan fragments produced by traditional positive-ion-mode reversed-phase LC-ESI MS/MS proteomic workflows and describe the specific fragmentation energy settings required to identify specific glycotopes presented on N- or O-linked glycopeptides in a typical proteomics MS/MS experiment.
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Affiliation(s)
- Nicholas J DeBono
- ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Edward S X Moh
- ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Nicolle H Packer
- ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
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5
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Hu Y, Schnaubelt M, Chen L, Zhang B, Hoang T, Lih TM, Zhang Z, Zhang H. MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses. Anal Chem 2024; 96:10145-10151. [PMID: 38869158 DOI: 10.1021/acs.analchem.3c01497] [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: 06/14/2024]
Abstract
Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.
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Affiliation(s)
- Yingwei Hu
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Michael Schnaubelt
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Li Chen
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Bai Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Trung Hoang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - T Mamie Lih
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Zhen Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Hui Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
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6
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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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7
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Polasky DA, Lu L, Yu F, Li K, Shortreed MR, Smith LM, Nesvizhskii AI. Quantitative proteome-wide O-glycoproteomics analysis with FragPipe. Anal Bioanal Chem 2024:10.1007/s00216-024-05382-x. [PMID: 38877149 DOI: 10.1007/s00216-024-05382-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/20/2024] [Accepted: 05/24/2024] [Indexed: 06/16/2024]
Abstract
Identification of O-glycopeptides from tandem mass spectrometry data is complicated by the near complete dissociation of O-glycans from the peptide during collisional activation and by the combinatorial explosion of possible glycoforms when glycans are retained intact in electron-based activation. The recent O-Pair search method provides an elegant solution to these problems, using a collisional activation scan to identify the peptide sequence and total glycan mass, and a follow-up electron-based activation scan to localize the glycosite(s) using a graph-based algorithm in a reduced search space. Our previous O-glycoproteomics methods with MSFragger-Glyco allowed for extremely fast and sensitive identification of O-glycopeptides from collisional activation data but had limited support for site localization of glycans and quantification of glycopeptides. Here, we report an improved pipeline for O-glycoproteomics analysis that provides proteome-wide, site-specific, quantitative results by incorporating the O-Pair method as a module within FragPipe. In addition to improved search speed and sensitivity, we add flexible options for oxonium ion-based filtering of glycans and support for a variety of MS acquisition methods and provide a comparison between all software tools currently capable of O-glycosite localization in proteome-wide searches.
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Affiliation(s)
- Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Lei Lu
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pharmaceutical Chemistry, University of San Francisco, San Francisco, CA, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Kai Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | | | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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Starosta RT, Lee AJ, Toolan ER, He M, Wongkittichote P, Daniel EJP, Radenkovic S, Budhraja R, Pandey A, Sharma J, Morava E, Nguyen H, Dickson PI. D-mannose as a new therapy for fucokinase deficiency-related congenital disorder of glycosylation (FCSK-CDG). Mol Genet Metab 2024; 142:108488. [PMID: 38735264 DOI: 10.1016/j.ymgme.2024.108488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 04/22/2024] [Accepted: 05/02/2024] [Indexed: 05/14/2024]
Abstract
INTRODUCTION Fucokinase deficiency-related congenital disorder of glycosylation (FCSK-CDG) is a rare autosomal recessive inborn error of metabolism characterized by a decreased flux through the salvage pathway of GDP-fucose biosynthesis due to a block in the recycling of L-fucose that exits the lysosome. FCSK-CDG has been described in 5 individuals to date in the medical literature, with a phenotype comprising global developmental delays/intellectual disability, hypotonia, abnormal myelination, posterior ocular disease, growth and feeding failure, immune deficiency, and chronic diarrhea, without clear therapeutic recommendations. PATIENT AND METHODS In a so far unreported FCSK-CDG patient, we studied proteomics and glycoproteomics in vitro in patient-derived fibroblasts and also performed in vivo glycomics, before and after treatment with either D-Mannose or L-Fucose. RESULTS We observed a marked increase in fucosylation after D-mannose supplementation in fibroblasts compared to treatment with L-Fucose. The patient was then treated with D-mannose at 850 mg/kg/d, with resolution of the chronic diarrhea, resolution of oral aversion, improved weight gain, and observed developmental gains. Serum N-glycan profiles showed an improvement in the abundance of fucosylated glycans after treatment. No treatment-attributed adverse effects were observed. CONCLUSION D-mannose is a promising new treatment for FCSK-CDG.
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Affiliation(s)
- Rodrigo Tzovenos Starosta
- Division of Medical Genetics and Genomics, Washington University School of Medicine, St. Louis, MO, USA; Division of Clinical Genetics and Metabolism, University of Colorado Anschutz, Aurora, CO, USA; Graduate Program in Science: Gastroenterology and Hepatology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
| | - Angela J Lee
- Division of Medical Genetics and Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Elizabeth R Toolan
- Division of Medical Genetics and Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Miao He
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Parith Wongkittichote
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Earnest James Paul Daniel
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Rohit Budhraja
- Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, MN, USA
| | - Akhilesh Pandey
- Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, MN, USA
| | - Jaiprakash Sharma
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
| | - Eva Morava
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA
| | - Hoanh Nguyen
- Division of Medical Genetics and Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Patricia I Dickson
- Division of Medical Genetics and Genomics, Washington University School of Medicine, St. Louis, MO, USA
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Cao W. Advancing mass spectrometry-based glycoproteomic software tools for comprehensive site-specific glycoproteome analysis. Curr Opin Chem Biol 2024; 80:102442. [PMID: 38460452 DOI: 10.1016/j.cbpa.2024.102442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/18/2024] [Accepted: 02/19/2024] [Indexed: 03/11/2024]
Abstract
Glycoproteome analysis at a site-specific level and proteome scale stands out as a highly promising approach for gaining insights into the intricate roles of glycans in biological systems. Recent years have witnessed an upsurge in the development of innovative methodologies tailored for precisely this purpose. Breakthroughs in mass spectrometry-based glycoproteomic techniques, enabling the identification, quantification, and systematic exploration of site-specific glycans, have significantly enhanced our capacity to comprehensively and thoroughly characterize glycoproteins. In this short review, we delve into novel tools in advancing site-specific glycoproteomic analysis and summarize pertinent studies published in the past two years. Lastly, we discuss the ongoing challenges and outline future prospects in the field, considering both the analytical strategies of mass spectrometry and the tools employed for data interpretation.
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Affiliation(s)
- Weiqian Cao
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, 200433, China.
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10
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Budhraja R, Radenkovic S, Jain A, Muffels IJJ, Ismaili MHA, Kozicz T, Pandey A, Morava E. Liposome-encapsulated mannose-1-phosphate therapy improves global N-glycosylation in different congenital disorders of glycosylation. Mol Genet Metab 2024; 142:108487. [PMID: 38733638 PMCID: PMC11166087 DOI: 10.1016/j.ymgme.2024.108487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/22/2024] [Accepted: 05/02/2024] [Indexed: 05/13/2024]
Abstract
Phosphomannomutase 2 (PMM2) converts mannose-6-phospahate to mannose-1-phosphate; the substrate for GDP-mannose, a building block of the glycosylation biosynthetic pathway. Pathogenic variants in the PMM2 gene have been shown to be associated with protein hypoglycosylation causing PMM2-congenital disorder of glycosylation (PMM2-CDG). While mannose supplementation improves glycosylation in vitro, but not in vivo, we hypothesized that liposomal delivery of mannose-1-phosphate could increase the stability and delivery of the activated sugar to enter the targeted compartments of cells. Thus, we studied the effect of liposome-encapsulated mannose-1-P (GLM101) on global protein glycosylation and on the cellular proteome in skin fibroblasts from individuals with PMM2-CDG, as well as in individuals with two N-glycosylation defects early in the pathway, namely ALG2-CDG and ALG11-CDG. We leveraged multiplexed proteomics and N-glycoproteomics in fibroblasts derived from different individuals with various pathogenic variants in PMM2, ALG2 and ALG11 genes. Proteomics data revealed a moderate but significant change in the abundance of some of the proteins in all CDG fibroblasts upon GLM101 treatment. On the other hand, N-glycoproteomics revealed the GLM101 treatment enhanced the expression levels of several high-mannose and complex/hybrid glycopeptides from numerous cellular proteins in individuals with defects in PMM2 and ALG2 genes. Both PMM2-CDG and ALG2-CDG exhibited several-fold increase in glycopeptides bearing Man6 and higher glycans and a decrease in Man5 and smaller glycan moieties, suggesting that GLM101 helps in the formation of mature glycoforms. These changes in protein glycosylation were observed in all individuals irrespective of their genetic variants. ALG11-CDG fibroblasts also showed increase in high mannose glycopeptides upon treatment; however, the improvement was not as dramatic as the other two CDG. Overall, our findings suggest that treatment with GLM101 overcomes the genetic block in the glycosylation pathway and can be used as a potential therapy for CDG with enzymatic defects in early steps in protein N-glycosylation.
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Affiliation(s)
- Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Silvia Radenkovic
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA
| | - Anu Jain
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Irena J J Muffels
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Tamas Kozicz
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA; Department of Anatomy, University of Pécs Medical School, 7624 Pécs, Hungary
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA; Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India.
| | - Eva Morava
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA; Department of Biophysics, University of Pécs Medical School, 7624 Pécs, Hungary.
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11
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Li Y, Wang J, Chen W, Lu H, Zhang Y. Comprehensive review of MS-based studies on N-glycoproteome and N-glycome of extracellular vesicles. Proteomics 2024; 24:e2300065. [PMID: 37474487 DOI: 10.1002/pmic.202300065] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 07/10/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023]
Abstract
Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that can be released by all type of cells. Whereas, as one of the most common post-translational modifications, glycosylation plays a vital role in various biological functions of EVs, such as EV biogenesis, sorting, and cellular recognition. Nevertheless, compared with studies on RNAs or proteins, those investigating the glycoconjugates of EVs are limited. An in-depth investigation of N-glycosylation of EVs can improve the understanding of the biological functions of EVs and help to exploit EVs from different perspectives. The general focus of studies on glycosylation of EVs primarily includes isolation and characterization of EVs, preparation of glycoproteome/glycome samples and MS analysis. However, the low content of EVs and non-standard separation methods for downstream analysis are the main limitations of these studies. In this review, we highlight the importance of glycopeptide/glycan enrichment and derivatization owing to the low abundance of glycoproteins and the low ionization efficiency of glycans. Diverse fragmentation patterns and professional analytical software are indispensable for analysing glycosylation via MS. Altogether, this review summarises recent studies on glycosylation of EVs, revealing the role of EVs in disease progression and their remarkable potential as biomarkers.
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Affiliation(s)
- Yang Li
- Institutes of Biomedical Sciences and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, P. R. China
| | - Jun Wang
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
| | - Weiyu Chen
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
| | - Haojie Lu
- Institutes of Biomedical Sciences and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, P. R. China
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
| | - Ying Zhang
- Institutes of Biomedical Sciences and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, P. R. China
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
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12
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Tian Y, Ma S, Wen L. Towards chemoenzymatic labeling strategies for profiling protein glycosylation. Curr Opin Chem Biol 2024; 80:102460. [PMID: 38678979 DOI: 10.1016/j.cbpa.2024.102460] [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: 12/26/2023] [Revised: 03/31/2024] [Accepted: 04/07/2024] [Indexed: 05/01/2024]
Abstract
Protein glycosylation is one of the most common and important post-translational modifications of proteins involved in regulating glycoprotein functions. The chemoenzymatic glycan labeling strategy allows rapid, efficient, and selective interrogation of glycoproteins. Glycoproteomics identifies protein glycosylation events at a large scale, providing information such as peptide sequences, glycan structures, and glycosylated sites. This review discusses the recent development of chemoenzymatic labeling strategies for glycoprotein analysis, mainly including glycoprotein and glycosite profiling. Furthermore, we highlight the chemoenzymatic enrichment approaches in mass spectrometry analysis for three classes of glycan modifications, including N-glycosylation, O-GlcNAcylation, and mucin-type O-glycosylation. Finally, we highlight the emerging trends in new tools and cutting-edge technologies available for glycoproteomic research.
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Affiliation(s)
- Yinping Tian
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Shengzhou Ma
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Liuqing Wen
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China; University of Chinese Academy of Sciences, Beijing, China.
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13
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Girgis M, Petruncio G, Russo P, Peyton S, Paige M, Campos D, Sanda M. Analysis of N- and O-linked site-specific glycosylation by ion mobility mass spectrometry: State of the art and future directions. Proteomics 2024; 24:e2300281. [PMID: 38171879 DOI: 10.1002/pmic.202300281] [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: 07/18/2023] [Revised: 11/22/2023] [Accepted: 12/05/2023] [Indexed: 01/05/2024]
Abstract
Glycosylation, the major post-translational modification of proteins, significantly increases the diversity of proteoforms. Glycans are involved in a variety of pivotal structural and functional roles of proteins, and changes in glycosylation are profoundly connected to the progression of numerous diseases. Mass spectrometry (MS) has emerged as the gold standard for glycan and glycopeptide analysis because of its high sensitivity and the wealth of fragmentation information that can be obtained. Various separation techniques have been employed to resolve glycan and glycopeptide isomers at the front end of the MS. However, differentiating structures of isobaric and isomeric glycopeptides constitutes a challenge in MS-based characterization. Many reports described the use of various ion mobility-mass spectrometry (IM-MS) techniques for glycomic analyses. Nevertheless, very few studies have focused on N- and O-linked site-specific glycopeptidomic analysis. Unlike glycomics, glycoproteomics presents a multitude of inherent challenges in microheterogeneity, which are further exacerbated by the lack of dedicated bioinformatics tools. In this review, we cover recent advances made towards the growing field of site-specific glycosylation analysis using IM-MS with a specific emphasis on the MS techniques and capabilities in resolving isomeric peptidoglycan structures. Furthermore, we discuss commonly used software that supports IM-MS data analysis of glycopeptides.
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Affiliation(s)
- Michael Girgis
- Department of Bioengineering, College of Engineering & Computing, George Mason University, Fairfax, Virginia, USA
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
| | - Gregory Petruncio
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
- Department of Chemistry & Biochemistry, College of Science, George Mason University, Fairfax, Virginia, USA
| | - Paul Russo
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia, USA
| | - Steven Peyton
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
| | - Mikell Paige
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
- Department of Chemistry & Biochemistry, College of Science, George Mason University, Fairfax, Virginia, USA
| | - Diana Campos
- Max-Planck-Institut fuer Herz- und Lungenforschung, Bad Nauheim, Germany
| | - Miloslav Sanda
- Max-Planck-Institut fuer Herz- und Lungenforschung, Bad Nauheim, Germany
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14
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Hu Z, Liu R, Gao W, Li J, Wang H, Tang K. A Fully Automated Online Enrichment and Separation System for Highly Reproducible and In-Depth Analysis of Intact Glycopeptide. Anal Chem 2024; 96:8822-8829. [PMID: 38698557 DOI: 10.1021/acs.analchem.4c01454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-μg sample amount, while a 10-μg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.
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Affiliation(s)
- Zhonghan Hu
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China
- Zhenhai Institute of Mass Spectrometry, Ningbo 315211, PR China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, PR China
| | - Rong Liu
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China
- Zhenhai Institute of Mass Spectrometry, Ningbo 315211, PR China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, PR China
| | - Wenqing Gao
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China
- Zhenhai Institute of Mass Spectrometry, Ningbo 315211, PR China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, PR China
| | - Junhui Li
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China
- Zhenhai Institute of Mass Spectrometry, Ningbo 315211, PR China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, PR China
| | - Hongxia Wang
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China
- Zhenhai Institute of Mass Spectrometry, Ningbo 315211, PR China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, PR China
| | - Keqi Tang
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China
- Zhenhai Institute of Mass Spectrometry, Ningbo 315211, PR China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, PR China
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15
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Meng X, Zhou Y, Xu L, Hu L, Wang C, Tian X, Zhang X, Hao Y, Cheng B, Ma J, Wang L, Liu J, Xie R. O-GlcNAcylation Facilitates the Interaction between Keratin 18 and Isocitrate Dehydrogenases and Potentially Influencing Cholangiocarcinoma Progression. ACS CENTRAL SCIENCE 2024; 10:1065-1083. [PMID: 38799671 PMCID: PMC11117311 DOI: 10.1021/acscentsci.4c00163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/06/2024] [Accepted: 04/10/2024] [Indexed: 05/29/2024]
Abstract
Glycosylation plays a pivotal role in the intricate landscape of human cholangiocarcinoma (CCA), actively participating in key pathophysiological processes driving tumor progression. Among the various glycosylation modifications, O-linked β-N-acetyl-glucosamine modification (O-GlcNAcylation) emerges as a dynamic regulator influencing diverse tumor-associated biological activities. In this study, we employed a state-of-the-art chemical proteomic approach to analyze intact glycopeptides, unveiling the critical role of O-GlcNAcylation in orchestrating Keratin 18 (K18) and its interplay with tricarboxylic acid (TCA) cycle enzymes, specifically isocitrate dehydrogenases (IDHs), to propel CCA progression. Our findings shed light on the mechanistic intricacies of O-GlcNAcylation, revealing that site-specific modification of K18 on Ser 30 serves as a stabilizing factor, amplifying the expression of cell cycle checkpoints. This molecular event intricately fosters cell cycle progression and augments cellular growth in CCA. Notably, the interaction between O-GlcNAcylated K18 and IDHs orchestrates metabolic reprogramming by down-regulating citrate and isocitrate levels while elevating α-ketoglutarate (α-KG). These metabolic shifts further contribute to the overall tumorigenic potential of CCA. Our study thus expands the current understanding of protein O-GlcNAcylation and introduces a new layer of complexity to post-translational control over metabolism and tumorigenesis.
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Affiliation(s)
- Xiangfeng Meng
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Yue Zhou
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Lei Xu
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Limu Hu
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Changjiang Wang
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Xiao Tian
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Xiang Zhang
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Yi Hao
- College
of
Chemistry and Molecular Engineering, Peking
University, Beijing 100871, China
| | - Bo Cheng
- School
of Pharmaceutical Sciences, Peking University, Beijing 100191, China
| | - Jing Ma
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
- Collaborative
Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210023, China
| | - Lei Wang
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Jialin Liu
- State
Key Laboratory of Medical Proteomics, Beijing Proteome Research Center,
National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Ran Xie
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
- Chemistry
and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210023, China
- Beijing
National Laboratory for Molecular Sciences, Beijing 100191, China
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16
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Garapati K, Jain A, Madden BJ, Mun DG, Sharma J, Budhraja R, Pandey A. Defining albumin as a glycoprotein with multiple N-linked glycosylation sites. J Transl Med 2024; 22:454. [PMID: 38741158 PMCID: PMC11090807 DOI: 10.1186/s12967-024-05000-5] [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: 01/12/2024] [Accepted: 02/14/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Glycosylation is an enzyme-catalyzed post-translational modification that is distinct from glycation and is present on a majority of plasma proteins. N-glycosylation occurs on asparagine residues predominantly within canonical N-glycosylation motifs (Asn-X-Ser/Thr) although non-canonical N-glycosylation motifs Asn-X-Cys/Val have also been reported. Albumin is the most abundant protein in plasma whose glycation is well-studied in diabetes mellitus. However, albumin has long been considered a non-glycosylated protein due to absence of canonical motifs. Albumin contains two non-canonical N-glycosylation motifs, of which one was recently reported to be glycosylated. METHODS We enriched abundant serum proteins to investigate their N-linked glycosylation followed by trypsin digestion and glycopeptide enrichment by size-exclusion or mixed-mode anion-exchange chromatography. Glycosylation at canonical as well as non-canonical sites was evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) of enriched glycopeptides. Deglycosylation analysis was performed to confirm N-linked glycosylation at non-canonical sites. Albumin-derived glycopeptides were fragmented by MS3 to confirm attached glycans. Parallel reaction monitoring was carried out on twenty additional samples to validate these findings. Bovine and rabbit albumin-derived glycopeptides were similarly analyzed by LC-MS/MS. RESULTS Human albumin is N-glycosylated at two non-canonical sites, Asn68 and Asn123. N-glycopeptides were detected at both sites bearing four complex sialylated glycans and validated by MS3-based fragmentation and deglycosylation studies. Targeted mass spectrometry confirmed glycosylation in twenty additional donor samples. Finally, the highly conserved Asn123 in bovine and rabbit serum albumin was also found to be glycosylated. CONCLUSIONS Albumin is a glycoprotein with conserved N-linked glycosylation sites that could have potential clinical applications.
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Affiliation(s)
- Kishore Garapati
- Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Anu Jain
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | | | - Dong-Gi Mun
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jyoti Sharma
- Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
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17
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Mu Y, Zhao S, Liu J, Liu Z, He J, Cao H, Zhao H, Wang C, Jin Y, Qi Y, Wang F. Assessment of the Conformation Stability and Glycosylation Heterogeneity of Lactoferrin by Native Mass Spectrometry. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:10089-10096. [PMID: 38626386 DOI: 10.1021/acs.jafc.3c08860] [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: 04/18/2024]
Abstract
Lactoferrin (LTF) has diverse biological activities and is widely used in functional foods and active additives. Nevertheless, evaluating the proteoform heterogeneity, conformational stability, and activity of LTF remains challenging during its production and storage processes. In this study, we describe the implementation of native mass spectrometry (nMS), glycoproteomics, and an antimicrobial activity assay to assess the quality of LTF. We systematically characterize the purity, glycosylation heterogeneity, conformation, and thermal stability of LTF samples from different sources and transient high-temperature treatments by using nMS and glycoproteomics. Meanwhile, the nMS peak intensity and antimicrobial activity of LTF samples after heat treatment decreased significantly, and the two values were positively correlated. The nMS results provide essential molecular insights into the conformational stability and glycosylation heterogeneity of different LTF samples. Our results underscore the great potential of nMS for LTF quality control and activity evaluation in industrial production.
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Affiliation(s)
- Yu Mu
- College of Food Science and Engineering, Ocean University of Dalian, Dalian 116023, China
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Shan Zhao
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Jing Liu
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- College of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Zheyi Liu
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Jian He
- Inner Mongolia Dairy Technology Research Institute Co., Ltd., Hohhot 010110, China
- Inner Mongolia National Center of Technology Innovation for Dairy Co. Ltd., Hohhot 010110, China
| | - Hongfang Cao
- Inner Mongolia Dairy Technology Research Institute Co., Ltd., Hohhot 010110, China
- Inner Mongolia National Center of Technology Innovation for Dairy Co. Ltd., Hohhot 010110, China
| | - Heng Zhao
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Caiyun Wang
- Inner Mongolia Dairy Technology Research Institute Co., Ltd., Hohhot 010110, China
- Inner Mongolia National Center of Technology Innovation for Dairy Co. Ltd., Hohhot 010110, China
| | - Yan Jin
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Yanxia Qi
- College of Food Science and Engineering, Ocean University of Dalian, Dalian 116023, China
| | - Fangjun Wang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- Inner Mongolia National Center of Technology Innovation for Dairy Co. Ltd., Hohhot 010110, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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18
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Yang J, Ostafe R, Bruening ML. In-Membrane Enrichment and Peptic Digestion to Facilitate Analysis of Monoclonal Antibody Glycosylation. Anal Chem 2024; 96:6347-6355. [PMID: 38607313 PMCID: PMC11283323 DOI: 10.1021/acs.analchem.4c00030] [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: 04/13/2024]
Abstract
The number of therapeutic monoclonal antibodies (mAbs) is growing rapidly due to their widespread use for treating various diseases and health conditions. Assessing the glycosylation profile of mAbs during production is essential to ensuring their safety and efficacy. This research aims to rapidly isolate and digest mAbs for liquid chromatography-tandem mass spectrometry (LC-MS/MS) identification of glycans and monitoring of glycosylation patterns, potentially during manufacturing. Immobilization of an Fc region-specific ligand, oFc20, in a porous membrane enables the enrichment of mAbs from cell culture supernatant and efficient elution with an acidic solution. Subsequent digestion of the mAb eluate occurred in a pepsin-modified membrane within 5 min. The procedure does not require alkylation and desalting, greatly shortening the sample preparation time. Subsequent LC-MS/MS analysis identified 11 major mAb N-glycan proteoforms and assessed the relative peak areas of the glycosylated peptides. This approach is suitable for the glycosylation profiling of various human IgG mAbs, including biosimilars and different IgG subclasses. The total time required for this workflow is less than 2 h, whereas the conventional enzymatic release and labeling of glycans can take much longer. Thus, the integrated membranes are suitable for facilitating the analysis of mAb glycosylation patterns.
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Affiliation(s)
- Junyan Yang
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, United States
| | - Raluca Ostafe
- Molecular Evolution, Protein Engineering and Production Facility; Purdue Institute for Inflammation, Immunology and Infection Diseases, Purdue University, West Lafayette, IN 47907, United States
| | - Merlin L. Bruening
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, United States
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, United States
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19
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Kang T, Budhraja R, Kim J, Joshi N, Garapati K, Pandey A. Global O-glycoproteome enrichment and analysis enabled by a combinatorial enzymatic workflow. CELL REPORTS METHODS 2024; 4:100744. [PMID: 38582075 PMCID: PMC11046030 DOI: 10.1016/j.crmeth.2024.100744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 01/25/2024] [Accepted: 03/18/2024] [Indexed: 04/08/2024]
Abstract
A comprehensive analysis of site-specific protein O-glycosylation is hindered by the absence of a consensus O-glycosylation motif, the diversity of O-glycan structures, and the lack of a universal enzyme that cleaves attached O-glycans. Here, we report the development of a robust O-glycoproteomic workflow for analyzing complex biological samples by combining four different strategies: removal of N-glycans, complementary digestion using O-glycoprotease (IMPa) with/without another protease, glycopeptide enrichment, and mass spectrometry with fragmentation of glycopeptides using stepped collision energy. Using this workflow, we cataloged 474 O-glycopeptides on 189 O-glycosites derived from 79 O-glycoproteins from human plasma. These data revealed O-glycosylation of several abundant proteins that have not been previously reported. Because many of the proteins that contained unannotated O-glycosylation sites have been extensively studied, we wished to confirm glycosylation at these sites in a targeted fashion. Thus, we analyzed selected purified proteins (kininogen-1, fetuin-A, fibrinogen, apolipoprotein E, and plasminogen) in independent experiments and validated the previously unknown O-glycosites.
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Affiliation(s)
- Taewook Kang
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Jinyong Kim
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Neha Joshi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
| | - Kishore Garapati
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Manipal Academy of Higher Education, Manipal, Karnataka 576104, India; Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA.
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20
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Adams TM, Zhao P, Kong R, Wells L. ppmFixer: a mass error adjustment for pGlyco3.0 to correct near-isobaric mismatches. Glycobiology 2024; 34:cwae006. [PMID: 38263491 PMCID: PMC11005163 DOI: 10.1093/glycob/cwae006] [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: 10/25/2023] [Revised: 01/07/2024] [Accepted: 01/08/2024] [Indexed: 01/25/2024] Open
Abstract
Modern glycoproteomics experiments require the use of search engines due to the generation of countless spectra. While these tools are valuable, manual validation of search engine results is often required for detailed analysis of glycopeptides as false-discovery rates are often not reliable for glycopeptide data. Near-isobaric mismatches are a common source of misidentifications for the popular glycopeptide-focused search engine pGlyco3.0, and in this technical note we share a strategy and script that improves the accuracy of the search utilizing two manually validated datasets of the glycoproteins CD16a and HIV-1 Env as proof-of-principle.
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Affiliation(s)
- Trevor M Adams
- Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Road, Athens 30602, Georgia
| | - Peng Zhao
- Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Road, Athens 30602, Georgia
| | - Rui Kong
- Department of Pathology and Laboratory Medicine, Emory Vaccine Center, Emory University, 7 Frist Ave, Atlanta 30317, Georgia
| | - Lance Wells
- Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Road, Athens 30602, Georgia
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21
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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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22
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Nalehua MR, Zaia J. A critical evaluation of ultrasensitive single-cell proteomics strategies. Anal Bioanal Chem 2024; 416:2359-2369. [PMID: 38358530 DOI: 10.1007/s00216-024-05171-6] [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: 09/25/2023] [Revised: 01/20/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024]
Abstract
Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.
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Affiliation(s)
| | - Joseph Zaia
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Biochemistry and Cell Biology, Boston University, Boston, MA, USA.
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23
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Yang Y, Fang Q. Prediction of glycopeptide fragment mass spectra by deep learning. Nat Commun 2024; 15:2448. [PMID: 38503734 PMCID: PMC10951270 DOI: 10.1038/s41467-024-46771-1] [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: 09/13/2023] [Accepted: 03/11/2024] [Indexed: 03/21/2024] Open
Abstract
Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we present DeepGlyco, a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrate that predicted spectral libraries can be used for data-independent acquisition glycoproteomics as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.
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Affiliation(s)
- Yi Yang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311200, China.
| | - Qun Fang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311200, China.
- Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
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24
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Collette AM, Hassan SA, Schmidt SI, Lara AJ, Yang W, Samara NL. An unusual dual sugar-binding lectin domain controls the substrate specificity of a mucin-type O-glycosyltransferase. SCIENCE ADVANCES 2024; 10:eadj8829. [PMID: 38416819 PMCID: PMC10901373 DOI: 10.1126/sciadv.adj8829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 01/23/2024] [Indexed: 03/01/2024]
Abstract
N-acetylgalactosaminyl-transferases (GalNAc-Ts) initiate mucin-type O-glycosylation, an abundant and complex posttranslational modification that regulates host-microbe interactions, tissue development, and metabolism. GalNAc-Ts contain a lectin domain consisting of three homologous repeats (α, β, and γ), where α and β can potentially interact with O-GalNAc on substrates to enhance activity toward a nearby acceptor Thr/Ser. The ubiquitous isoenzyme GalNAc-T1 modulates heart development, immunity, and SARS-CoV-2 infectivity, but its substrates are largely unknown. Here, we show that both α and β in GalNAc-T1 uniquely orchestrate the O-glycosylation of various glycopeptide substrates. The α repeat directs O-glycosylation to acceptor sites carboxyl-terminal to an existing GalNAc, while the β repeat directs O-glycosylation to amino-terminal sites. In addition, GalNAc-T1 incorporates α and β into various substrate binding modes to cooperatively increase the specificity toward an acceptor site located between two existing O-glycans. Our studies highlight a unique mechanism by which dual lectin repeats expand substrate specificity and provide crucial information for identifying the biological substrates of GalNAc-T1.
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Affiliation(s)
- Abbie M Collette
- Structural Biochemistry Unit, NIDCR, NIH, Bethesda, MD 20892, USA
| | - Sergio A Hassan
- Bioinformatics and Computational Biosciences Branch, OCICB, NIAID, NIH, Bethesda, MD 20892, USA
| | - Susan I Schmidt
- MICaB Program, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Alexander J Lara
- Section on Biological Chemistry, NIDCR, NIH, Bethesda, MD 20892, USA
| | - Weiming Yang
- Section on Biological Chemistry, NIDCR, NIH, Bethesda, MD 20892, USA
| | - Nadine L Samara
- Structural Biochemistry Unit, NIDCR, NIH, Bethesda, MD 20892, USA
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25
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Xu X, Yin K, Xu S, Wang Z, Wu R. Mass spectrometry-based methods for investigating the dynamics and organization of the surfaceome: exploring potential clinical implications. Expert Rev Proteomics 2024; 21:99-113. [PMID: 38300624 PMCID: PMC10928381 DOI: 10.1080/14789450.2024.2314148] [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: 11/22/2023] [Accepted: 01/16/2024] [Indexed: 02/02/2024]
Abstract
INTRODUCTION Cell-surface proteins are extremely important for many cellular events, such as regulating cell-cell communication and cell-matrix interactions. Aberrant alterations in surface protein expression, modification (especially glycosylation), and interactions are directly related to human diseases. Systematic investigation of surface proteins advances our understanding of protein functions, cellular activities, and disease mechanisms, which will lead to identifying surface proteins as disease biomarkers and drug targets. AREAS COVERED In this review, we summarize mass spectrometry (MS)-based proteomics methods for global analysis of cell-surface proteins. Then, investigations of the dynamics of surface proteins are discussed. Furthermore, we summarize the studies for the surfaceome interaction networks. Additionally, biological applications of MS-based surfaceome analysis are included, particularly highlighting the significance in biomarker identification, drug development, and immunotherapies. EXPERT OPINION Modern MS-based proteomics provides an opportunity to systematically characterize proteins. However, due to the complexity of cell-surface proteins, the labor-intensive workflow, and the limit of clinical samples, comprehensive characterization of the surfaceome remains extraordinarily challenging, especially in clinical studies. Developing and optimizing surfaceome enrichment methods and utilizing automated sample preparation workflow can expand the applications of surfaceome analysis and deepen our understanding of the functions of cell-surface proteins.
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Affiliation(s)
- Xing Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Kejun Yin
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Senhan Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Zeyu Wang
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Ronghu Wu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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26
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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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27
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Yang J, Zhao Y, Wang X, Yang J, Tang K, Liu J. N-linked glycoproteome analysis reveals central glycosylated proteins involved in response to wheat yellow mosaic virus in wheat. Int J Biol Macromol 2023; 253:126818. [PMID: 37690635 DOI: 10.1016/j.ijbiomac.2023.126818] [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: 07/08/2023] [Revised: 09/06/2023] [Accepted: 09/07/2023] [Indexed: 09/12/2023]
Abstract
Glycosylation is an important proteins post-translational modification and is involved in protein folding, stability and enzymatic activity, which plays a crucial role in regulating protein function in plants. Here, we report for the first time on the changes of N-glycoproteome in wheat response to wheat yellow mosaic virus (WYMV) infection. Quantitative analyses of N-linked glycoproteome were performed in wheat without and with WYMV infection by ZIC-HILIC enrichment method combined with LC-MS/MS. Altogether 1160 N-glycopeptides and 971 N-glycosylated sites corresponding to 734 N-glycoproteins were identified, of which 64 N-glycopeptides and 64 N-glycosylated sites in 60 N-glycoproteins were significantly differentially expressed. Two conserved typical N-glycosylation motifs N-X-T and N-X-S and a nontypical motifs N-X-C were enriched in wheat. Gene Ontology analysis showed that most differentially expressed proteins were mainly enriched in metabolic process, catalytic activity and response to stress. Kyoto Encyclopedia of Genes and Genomes analysis indicated that two significantly changed glycoproteins were specifically related to plant-pathogen interaction. Furthermore, we found that over-expression of TaCERK reduced WYMV accumulation. Glycosylation site mutation further suggested that N-glycosylation of TaCERK could regulate wheat resistance to WYMV. This study provides a new insight for the regulation of protein N-glycosylation in defense response of plant.
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Affiliation(s)
- Jiaqian Yang
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass spectrometry and Clinical Application, School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, China; Zhenhai Institute of Mass Spectrometry, Ningbo 315211, China
| | - Yingjie Zhao
- State Key Laboratory for Quality and Safety of Agro-products, Key Laboratory of Biotechnology in Plant Protection of Ministry of Agriculture and Rural Affairs and Zhejiang Province, Institute of Plant Virology, Ningbo University, Ningbo 315211, China
| | - Xia Wang
- State Key Laboratory for Quality and Safety of Agro-products, Key Laboratory of Biotechnology in Plant Protection of Ministry of Agriculture and Rural Affairs and Zhejiang Province, Institute of Plant Virology, Ningbo University, Ningbo 315211, China
| | - Jian Yang
- State Key Laboratory for Quality and Safety of Agro-products, Key Laboratory of Biotechnology in Plant Protection of Ministry of Agriculture and Rural Affairs and Zhejiang Province, Institute of Plant Virology, Ningbo University, Ningbo 315211, China
| | - Keqi Tang
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass spectrometry and Clinical Application, School of Material Science and Chemical Engineering, Ningbo University, Ningbo 315211, China; Zhenhai Institute of Mass Spectrometry, Ningbo 315211, China.
| | - Jiaqian Liu
- State Key Laboratory for Quality and Safety of Agro-products, Key Laboratory of Biotechnology in Plant Protection of Ministry of Agriculture and Rural Affairs and Zhejiang Province, Institute of Plant Virology, Ningbo University, Ningbo 315211, China.
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28
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Wang X, Li H, Wang Z, Chen J, Chen W, Zhou X, Zhang L, Xu S, Gao XD, Yang G. Site- and Structure-Specific Glycosylation Signatures of Bovine, Caprine, Porcine, and Human Milk-Derived Extracellular Vesicles. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:20826-20837. [PMID: 38096130 DOI: 10.1021/acs.jafc.3c06439] [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: 12/28/2023]
Abstract
Extracellular vesicles (EVs) are membrane-bound vesicles released by living cells. As vesicles for macromolecule transmission and intercellular communication, EVs are broadly applied in clinical diagnosis and biomimetic drug delivery. Milk-derived EVs (MEVs) are an ideal choice for scale-up applications because they exhibit biocompatibility and are easily obtained. Herein, intact glycopeptides in MEVs from bovines, caprines, porcines, and humans were comprehensively analyzed by high-resolution mass spectrometry using the sceHCD, followed by the EThcD fragment method, revealing that protein glycosylation is abundant and heterogeneous in MEVs. The dominant glycans in all MEVs were sialic acid-modified N-linked glycans (over 50%). A couple of species-specific glycans were also characterized, which are potentially markers of different original EVs. Interestingly, the Neu5Gc-modified glycans were enriched in caprine milk-derived EVs (58 ± 2%). Heterogeneity of MEV protein glycosylation was observed for glycosites and glycan compositions, and the structural heterogeneity of protein glycosylation was also identified and validated. The glycosignatures of EV biogenesis- and endocytosis-related proteins (CD63 and MFGE8) were significantly different in these four species. Overall, we comprehensively characterized the glycosylation signature of MEVs from four different species and provided insight into protein glycosylation related to drug target delivery.
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Affiliation(s)
- Xiuyuan Wang
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Hanjie Li
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Zibo Wang
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Jingru Chen
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Wenyan Chen
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Xiaoman Zhou
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Lina Zhang
- State Key Laboratory of Food Science & Technology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Shiqian Xu
- Henan XinDa Livestock Co., Ltd., Zhengzhou, Henan 450001, China
| | - Xiao-Dong Gao
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Ganglong Yang
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
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29
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Tian X, Zheng L, Wang C, Han Y, Li Y, Cui T, Liu J, Liu C, Jia G, Yang L, Hsu Y, Zeng C, Ding L, Wang C, Cheng B, Wang M, Xie R. Selenium-based metabolic oligosaccharide engineering strategy for quantitative glycan detection. Nat Commun 2023; 14:8281. [PMID: 38092825 PMCID: PMC10719347 DOI: 10.1038/s41467-023-44118-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023] Open
Abstract
Metabolic oligosaccharide engineering (MOE) is a classical chemical approach to perturb, profile and perceive glycans in physiological systems, but probes upon bioorthogonal reaction require accessibility and the background signal readout makes it challenging to achieve glycan quantification. Here we develop SeMOE, a selenium-based metabolic oligosaccharide engineering strategy that concisely combines elemental analysis and MOE,enabling the mass spectrometric imaging of glycome. We also demonstrate that the new-to-nature SeMOE probes allow for detection, quantitative measurement and visualization of glycans in diverse biological contexts. We also show that chemical reporters on conventional MOE can be integrated into a bifunctional SeMOE probe to provide multimodality signal readouts. SeMOE thus provides a convenient and simplified method to explore the glyco-world.
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Affiliation(s)
- Xiao Tian
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Lingna Zheng
- CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Changjiang Wang
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Yida Han
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Yujie Li
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Tongxiao Cui
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Jialin Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Chuanming Liu
- Center for Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China
| | - Guogeng Jia
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Lujie Yang
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Yi Hsu
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Chen Zeng
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Lijun Ding
- Center for Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China
| | - Chu Wang
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Bo Cheng
- School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Meng Wang
- CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
| | - Ran Xie
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China.
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30
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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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31
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Chmielewski D, Wilson EA, Pintilie G, Zhao P, Chen M, Schmid MF, Simmons G, Wells L, Jin J, Singharoy A, Chiu W. Structural insights into the modulation of coronavirus spike tilting and infectivity by hinge glycans. Nat Commun 2023; 14:7175. [PMID: 37935678 PMCID: PMC10630519 DOI: 10.1038/s41467-023-42836-9] [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: 02/05/2023] [Accepted: 10/23/2023] [Indexed: 11/09/2023] Open
Abstract
Coronavirus spike glycoproteins presented on the virion surface mediate receptor binding, and membrane fusion during virus entry and constitute the primary target for vaccine and drug development. How the structure dynamics of the full-length spikes incorporated in viral lipid envelope correlates with the virus infectivity remains poorly understood. Here we present structures and distributions of native spike conformations on vitrified human coronavirus NL63 (HCoV-NL63) virions without chemical fixation by cryogenic electron tomography (cryoET) and subtomogram averaging, along with site-specific glycan composition and occupancy determined by mass spectrometry. The higher oligomannose glycan shield on HCoV-NL63 spikes than on SARS-CoV-2 spikes correlates with stronger immune evasion of HCoV-NL63. Incorporation of cryoET-derived native spike conformations into all-atom molecular dynamic simulations elucidate the conformational landscape of the glycosylated, full-length spike that reveals a role of hinge glycans in modulating spike bending. We show that glycosylation at N1242 at the upper portion of the stalk is responsible for the extensive orientational freedom of the spike crown. Subsequent infectivity assays implicated involvement of N1242-glyan in virus entry. Our results suggest a potential therapeutic target site for HCoV-NL63.
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Affiliation(s)
- David Chmielewski
- Biophysics Graduate Program, Stanford University, Stanford, CA, 94305, USA
| | - Eric A Wilson
- School of Molecular Sciences, Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Grigore Pintilie
- Department of Bioengineering, and of Microbiology and Immunology, Stanford University, Stanford, CA, 94305, USA
| | - Peng Zhao
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, 30602, USA
| | - Muyuan Chen
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, 94025, USA
| | - Michael F Schmid
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, 94025, USA
| | - Graham Simmons
- Vitalant Research Institute, San Francisco, CA, 94118, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, 94143, USA
| | - Lance Wells
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, 30602, USA
| | - Jing Jin
- Department of Bioengineering, and of Microbiology and Immunology, Stanford University, Stanford, CA, 94305, USA.
- Vitalant Research Institute, San Francisco, CA, 94118, USA.
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, 94143, USA.
| | - Abhishek Singharoy
- School of Molecular Sciences, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
| | - Wah Chiu
- Biophysics Graduate Program, Stanford University, Stanford, CA, 94305, USA.
- Department of Bioengineering, and of Microbiology and Immunology, Stanford University, Stanford, CA, 94305, USA.
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, 94025, USA.
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32
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Chen J, Yang L, Li C, Zhang L, Gao W, Xu R, Tian R. Chemical Proteomic Approach for In-Depth Glycosylation Profiling of Plasma Carcinoembryonic Antigen in Cancer Patients. Mol Cell Proteomics 2023; 22:100662. [PMID: 37820924 PMCID: PMC10652130 DOI: 10.1016/j.mcpro.2023.100662] [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: 07/04/2023] [Revised: 09/06/2023] [Accepted: 10/07/2023] [Indexed: 10/13/2023] Open
Abstract
Carcinoembryonic antigen (CEA) of human plasma is a biomarker of many cancer diseases, and its N-glycosylation accounts for 60% of molecular mass. It is highly desirable to characterize its glycoforms for providing additional dimension of features to increase its performance in prognosis and diagnosis of cancers. However, to systematically characterize its site-specific glycosylation is challenging because of its low abundance. Here, we developed a highly sensitive strategy for in-depth glycosylation profiling of plasma CEA through chemical proteomics combined with multienzymatic digestion. A trifunctional probe was utilized to generate covalent bond of plasma CEA and its antibody upon UV irradiation. As low as 1 ng/ml CEA in plasma could be captured and digested with trypsin and chymotrypsin for intact glycopeptide characterization. Twenty six of 28 potential N-glycosylation sites were well identified, which were the most comprehensive N-glycosylation site characterization of CEA on intact glycopeptide level as far as we known. Importantly, this strategy was applied to the glycosylation analysis of plasma CEA in cancer patients. Differential site-specific glycoforms of plasma CEA were observed in patients with colorectal cancers (CRCs) and lung cancer. The distributions of site-specific glycoforms were different as the progression of CRC, and most site-specific glycoforms were overexpressed in stage II of CRC. Overall, we established a highly sensitive chemical proteomic method to profile site-specific glycosylation of plasma CEA, which should generally applicable to other well-established cancer glycoprotein biomarkers for improving their cancer diagnosis and monitoring performance.
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Affiliation(s)
- Jin Chen
- Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, China; Clinical Center for Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China
| | - Lijun Yang
- Department of Oncology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China; The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Chang Li
- Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, China
| | - Luobin Zhang
- Department of Oncology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Weina Gao
- Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, China
| | - Ruilian Xu
- Department of Oncology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
| | - Ruijun Tian
- Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, China.
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33
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Yang W, Tian E, Chernish A, McCluggage P, Dalal K, Lara A, Ten Hagen KG, Tabak LA. Quantitative mapping of the in vivo O-GalNAc glycoproteome in mouse tissues identifies GalNAc-T2 O-glycosites in metabolic disorder. Proc Natl Acad Sci U S A 2023; 120:e2303703120. [PMID: 37862385 PMCID: PMC10614836 DOI: 10.1073/pnas.2303703120] [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: 03/05/2023] [Accepted: 09/03/2023] [Indexed: 10/22/2023] Open
Abstract
The family of GalNAc-Ts (GalNAcpolypeptide:N-Acetylgalactosaminyl transferases) catalyzes the first committed step in the synthesis of O-glycans, which is an abundant and biologically important protein modification. Abnormalities in the activity of individual GalNAc-Ts can result in congenital disorders of O-glycosylation (CDG) and influence a broad array of biological functions. How site-specific O-glycans regulate biology is unclear. Compiling in vivo O-glycosites would be an invaluable step in determining the function of site-specific O-glycans. We integrated chemical and enzymatic conditions that cleave O-glycosites, a higher-energy dissociation product ions-triggered electron-transfer/higher-energy collision dissociation mass spectrometry (MS) workflow and software to study nine mouse tissues and whole blood. We identified 2,154 O-glycosites from 595 glycoproteins. The O-glycosites and glycoproteins displayed consensus motifs and shared functions as classified by Gene Ontology terms. Limited overlap of O-glycosites was observed with protein O-GlcNAcylation and phosphorylation sites. Quantitative glycoproteomics and proteomics revealed a tissue-specific regulation of O-glycosites that the differential expression of Galnt isoenzymes in tissues partly contributes to. We examined the Galnt2-null mouse model, which phenocopies congenital disorder of glycosylation involving GALNT2 and revealed a network of glycoproteins that lack GalNAc-T2-specific O-glycans. The known direct and indirect functions of these glycoproteins appear consistent with the complex metabolic phenotypes observed in the Galnt2-null animals. Through this study and interrogation of databases and the literature, we have compiled an atlas of experimentally identified mouse O-glycosites consisting of 2,925 O-glycosites from 758 glycoproteins.
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Affiliation(s)
- Weiming Yang
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - E. Tian
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Aliona Chernish
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Peggy McCluggage
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Kruti Dalal
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Alexander Lara
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Kelly G. Ten Hagen
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Lawrence A. Tabak
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
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34
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Kuo CW, Chang NE, Yu PY, Yang TJ, Hsu STD, Khoo KH. An N-glycopeptide MS/MS data analysis workflow leveraging two complementary glycoproteomic software tools for more confident identification and assignments. Proteomics 2023; 23:e2300143. [PMID: 37271932 DOI: 10.1002/pmic.202300143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 05/18/2023] [Accepted: 05/22/2023] [Indexed: 06/06/2023]
Abstract
Complete coverage of all N-glycosylation sites on the SARS-CoV2 spike protein would require the use of multiple proteases in addition to trypsin. Subsequent identification of the resulting glycopeptides by searching against database often introduces assignment errors due to similar mass differences between different permutations of amino acids and glycosyl residues. By manually interpreting the individual MS2 spectra, we report here the common sources of errors in assignment, especially those introduced by the use of chymotrypsin. We show that by applying a stringent threshold of acceptance, erroneous assignment by the commonly used Byonic software can be controlled within 15%, which can be reduced further if only those also confidently identified by a different search engine, pGlyco3, were considered. A representative site-specific N-glycosylation pattern could be constructed based on quantifying only the overlapping subset of N-glycopeptides identified at higher confidence. Applying the two complimentary glycoproteomic software in a concerted data analysis workflow, we found and confirmed that glycosylation at several sites of an unstable Omicron spike protein differed significantly from those of the stable trimeric product of the parental D614G variant.
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Affiliation(s)
- Chu-Wei Kuo
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
| | - Ning-En Chang
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei, Taiwan
| | - Pei-Yu Yu
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
| | - Tzu-Jing Yang
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei, Taiwan
| | - Shang-Te Danny Hsu
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei, Taiwan
- International Institute for Sustainability with Knotted Chiral Meta Matter, Hiroshima University, Higashihiroshima, Japan
| | - Kay-Hooi Khoo
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei, Taiwan
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35
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Suttapitugsakul S, Matsumoto Y, Aryal RP, Cummings RD. Large-Scale and Site-Specific Mapping of the Murine Brain O-Glycoproteome with IMPa. Anal Chem 2023; 95:13423-13430. [PMID: 37624755 PMCID: PMC10501376 DOI: 10.1021/acs.analchem.3c00408] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 07/16/2023] [Indexed: 08/27/2023]
Abstract
Altered protein glycosylation is typically associated with cognitive defects and other phenotypes, but there is a lack of knowledge about the brain glycoproteome. Here, we used the newly available O-glycoprotease IMPa from Pseudomonas aeruginosa for comprehensive O-glycoproteomic analyses of the mouse brain. In this approach, total tryptic glycopeptides were prepared, extracted, purified, and conjugated to a solid support before an enzymatic cleavage by IMPa. O-glycopeptides were analyzed by electron-transfer/higher-energy collision dissociation (EThcD), which permits site-specific and global analysis of all types of O-glycans. We developed two complementary approaches for the analysis of the total O-glycoproteome using HEK293 cells and derivatives. The results demonstrated that IMPa and EThcD facilitate the confident localization of O-glycans on glycopeptides. We then applied these approaches to characterize the O-glycoproteome of the mouse brain, which revealed the high frequency of various sialylated O-glycans along with the unusual presence of the Tn antigen. Unexpectedly, the results demonstrated that glycoproteins in the brain O-glycoproteome only partly overlap with those reported for the brain N-glycoproteome. These approaches will aid in identifying the novel O-glycoproteomes of different cells and tissues and foster clinical and translational insights into the functions of protein O-glycosylation in the brain and other organs.
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Affiliation(s)
- Suttipong Suttapitugsakul
- Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical
School, Boston, Massachusetts 02215, United States
| | | | - Rajindra P. Aryal
- Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical
School, Boston, Massachusetts 02215, United States
| | - Richard D. Cummings
- Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical
School, Boston, Massachusetts 02215, United States
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36
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Liu J, Cheng B, Fan X, Zhou X, Wang J, Zhou W, Li H, Zeng W, Yang P, Chen X. Click-iG: Simultaneous Enrichment and Profiling of Intact N-linked, O-GalNAc, and O-GlcNAcylated Glycopeptides. Angew Chem Int Ed Engl 2023; 62:e202303410. [PMID: 37431278 DOI: 10.1002/anie.202303410] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/08/2023] [Accepted: 07/10/2023] [Indexed: 07/12/2023]
Abstract
Proteins are ubiquitously modified with glycans of varied chemical structures through distinct glycosidic linkages, making the landscape of protein glycosylation challenging to map. Profiling of intact glycopeptides with mass spectrometry (MS) has recently emerged as a powerful tool for revealing matched information of the glycosylation sites and attached glycans (i.e., intact glycosites), but is largely limited to individual glycosylation types. Herein, we describe Click-iG, which integrates metabolic labeling of glycans with clickable unnatural sugars, an optimized MS method, and a tailored version of pGlyco3 software to enable simultaneous enrichment and profiling of three types of intact glycopeptides: N-linked, mucin-type O-linked, and O-GlcNAcylated glycopeptides. We demonstrate the utility of Click-iG by the identification of thousands of intact glycosites in cell lines and living mice. From the mouse lung, heart, and spleen, a total of 2053 intact N-glycosites, 262 intact O-GalNAc glycosites, and 1947 O-GlcNAcylation sites were identified. Click-iG-enabled comprehensive coverage of the protein glycosylation landscape lays the foundation for interrogating crosstalk between different glycosylation pathways.
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Affiliation(s)
- Jialin Liu
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
- Institute of Biomedical Sciences and Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Bo Cheng
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Xinqi Fan
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Xinyue Zhou
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Jiankun Wang
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Wen Zhou
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Hengyu Li
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Wenfeng Zeng
- Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) and Institute of Computing Technology, CAS, Beijing, 100190, China
| | - Pengyuan Yang
- Institute of Biomedical Sciences and Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Xing Chen
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
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37
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Downs M, Zaia J, Sethi MK. Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases. MASS SPECTROMETRY REVIEWS 2023; 42:1848-1875. [PMID: 35719114 PMCID: PMC9763553 DOI: 10.1002/mas.21792] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/12/2022] [Accepted: 05/24/2022] [Indexed: 06/15/2023]
Abstract
The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.
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Affiliation(s)
- Margaret Downs
- Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University, Boston, Massachusetts, USA
| | - Joseph Zaia
- Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University, Boston, Massachusetts, USA
- Bioinformatics Program, Boston University, Boston, Massachusetts, USA
| | - Manveen K Sethi
- Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University, Boston, Massachusetts, USA
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38
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Ligezka AN, Budhraja R, Nishiyama Y, Fiesel FC, Preston G, Edmondson A, Ranatunga W, Van Hove JLK, Watzlawik JO, Springer W, Pandey A, Morava E, Kozicz T. Interplay of Impaired Cellular Bioenergetics and Autophagy in PMM2-CDG. Genes (Basel) 2023; 14:1585. [PMID: 37628636 PMCID: PMC10454768 DOI: 10.3390/genes14081585] [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: 06/23/2023] [Revised: 07/25/2023] [Accepted: 08/02/2023] [Indexed: 08/27/2023] Open
Abstract
Congenital disorders of glycosylation (CDG) and mitochondrial disorders are multisystem disorders with overlapping symptomatology. Pathogenic variants in the PMM2 gene lead to abnormal N-linked glycosylation. This disruption in glycosylation can induce endoplasmic reticulum stress, contributing to the disease pathology. Although impaired mitochondrial dysfunction has been reported in some CDG, cellular bioenergetics has never been evaluated in detail in PMM2-CDG. This prompted us to evaluate mitochondrial function and autophagy/mitophagy in vitro in PMM2 patient-derived fibroblast lines of differing genotypes from our natural history study. We found secondary mitochondrial dysfunction in PMM2-CDG. This dysfunction was evidenced by decreased mitochondrial maximal and ATP-linked respiration, as well as decreased complex I function of the mitochondrial electron transport chain. Our study also revealed altered autophagy in PMM2-CDG patient-derived fibroblast lines. This was marked by an increased abundance of the autophagosome marker LC3-II. Additionally, changes in the abundance and glycosylation of proteins in the autophagy and mitophagy pathways further indicated dysregulation of these cellular processes. Interestingly, serum sorbitol levels (a biomarker of disease severity) and the CDG severity score showed an inverse correlation with the abundance of the autophagosome marker LC3-II. This suggests that autophagy may act as a modulator of biochemical and clinical markers of disease severity in PMM2-CDG. Overall, our research sheds light on the complex interplay between glycosylation, mitochondrial function, and autophagy/mitophagy in PMM2-CDG. Manipulating mitochondrial dysfunction and alterations in autophagy/mitophagy pathways could offer therapeutic benefits when combined with existing treatments for PMM2-CDG.
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Affiliation(s)
- Anna N. Ligezka
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA
| | - Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Systems Biology and Translational Medicine Laboratory, Mayo Clinic, Rochester, MN 55905, USA
| | - Yurika Nishiyama
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA
| | - Fabienne C. Fiesel
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
- Neuroscience PhD Program, Mayo Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Graeme Preston
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA
| | - Andrew Edmondson
- Department of Pediatrics, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | | | - Johan L. K. Van Hove
- Department of Pediatrics, Section of Clinical Genetics and Metabolism, University of Colorado, Aurora, CO 80309, USA
| | - Jens O. Watzlawik
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Wolfdieter Springer
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
- Neuroscience PhD Program, Mayo Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Systems Biology and Translational Medicine Laboratory, Mayo Clinic, Rochester, MN 55905, USA
- Manipal Academy of Higher Education, Manipal 576104, Karnataka, India
| | - Eva Morava
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA
- Department of Biophysics, University of Pecs Medical School, 7624 Pecs, Hungary
| | - Tamas Kozicz
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, USA
- Department of Anatomy, University of Pecs Medical School, 7624 Pecs, Hungary
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39
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Li Y, Guo W, Zhang Q, Yang B, Zhang Y, Yang Y, Liu G, Pan L, Zhang W, Kong D. Improved analysis ZIC-HILIC-HCD-Orbitrap method for mapping the glycopeptide by mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2023; 1228:123852. [PMID: 37633008 DOI: 10.1016/j.jchromb.2023.123852] [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: 05/29/2023] [Revised: 07/29/2023] [Accepted: 08/15/2023] [Indexed: 08/28/2023]
Abstract
Glycosylation is one of the most common post-translational modifications (PTMs). Protein glycosylation analysis is the bottleneck to deeply understand their functions. At present, the LC-MS analysis of glycosylated post-translational modification is mainly focused on the analysis of glycopeptides. However, the factors affecting the identification of glycopeptides were not fully elucidated. In the paper, we have carefully studied the factors, e.g., HILIC materials, search engines, protein amount, gradient duration, extraction solution, etc. According to the results, HILIC materials were the most important factors affecting the glycopeptides identification, and the amphoteric sulfoalkyl betaine stationary phase enriched glycopeptides 6-fold more compared to the amphiphilic ion-bonded fully porous spherical silica stationary phase. We explored the influence of the extraction solutions on glycan identification. Comparing sodium dodecyl sulfate (SDS) and urea (UA), the results showed that N-glycolylneuraminic acid (NeuGc) type of glycan content was found to be increased 1.4-fold in the SDS compared to UA. Besides, we explored the influence of the search engine on glycopeptide identification. Comparing pGlyco3.0 and MSFragger-Glyco, it was observed that pGlyco3.0 outperformed MSFragger-Glyco in identifying glycopeptides. Then, using our optimized method we found that there was a significant difference in the distribution of monosaccharide types in plasma and brain tissue, e.g., the content of NeuAc in brain was 5-fold higher than that in plasma. To importantly, two glycoproteins (Neurexin-2 and SUN domain-containing protein 2) were also found for the first time by our method. In summary, we have comprehensively studied the factors influencing glycopeptide identification than any previous research, and the optimized method could be widely used for identifying the glycoproteins or glycolpeptides biomarkers for disease detection and therapeutic targets.
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Affiliation(s)
- Yahui Li
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Wenyan Guo
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Qingning Zhang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Bingkun Yang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China; School of Pharmacy, Hebei Medical University, Shijiazhuang, China
| | - Yuyu Zhang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Yi Yang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China; The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Guangyuan Liu
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Liangyu Pan
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Wei Zhang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China.
| | - Dezhi Kong
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China.
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40
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Costa J, Hayes C, Lisacek F. Protein glycosylation and glycoinformatics for novel biomarker discovery in neurodegenerative diseases. Ageing Res Rev 2023; 89:101991. [PMID: 37348818 DOI: 10.1016/j.arr.2023.101991] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/25/2023] [Accepted: 06/18/2023] [Indexed: 06/24/2023]
Abstract
Glycosylation is a common post-translational modification of brain proteins including cell surface adhesion molecules, synaptic proteins, receptors and channels, as well as intracellular proteins, with implications in brain development and functions. Using advanced state-of-the-art glycomics and glycoproteomics technologies in conjunction with glycoinformatics resources, characteristic glycosylation profiles in brain tissues are increasingly reported in the literature and growing evidence shows deregulation of glycosylation in central nervous system disorders, including aging associated neurodegenerative diseases. Glycan signatures characteristic of brain tissue are also frequently described in cerebrospinal fluid due to its enrichment in brain-derived molecules. A detailed structural analysis of brain and cerebrospinal fluid glycans collected in publications in healthy and neurodegenerative conditions was undertaken and data was compiled to create a browsable dedicated set in the GlyConnect database of glycoproteins (https://glyconnect.expasy.org/brain). The shared molecular composition of cerebrospinal fluid with brain enhances the likelihood of novel glycobiomarker discovery for neurodegeneration, which may aid in unveiling disease mechanisms, therefore, providing with novel therapeutic targets as well as diagnostic and progression monitoring tools.
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Affiliation(s)
- Júlia Costa
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, Portugal.
| | - Catherine Hayes
- Proteome Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland; Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland; Section of Biology, University of Geneva, CH-1211 Geneva, Switzerland
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41
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Geiszler DJ, Polasky DA, Yu F, Nesvizhskii AI. Detecting diagnostic features in MS/MS spectra of post-translationally modified peptides. Nat Commun 2023; 14:4132. [PMID: 37438360 DOI: 10.1038/s41467-023-39828-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 06/23/2023] [Indexed: 07/14/2023] Open
Abstract
Post-translational modifications are an area of great interest in mass spectrometry-based proteomics, with a surge in methods to detect them in recent years. However, post-translational modifications can introduce complexity into proteomics searches by fragmenting in unexpected ways, ultimately hindering the detection of modified peptides. To address these deficiencies, we present a fully automated method to find diagnostic spectral features for any modification. The features can be incorporated into proteomics search engines to improve modified peptide recovery and localization. We show the utility of this approach by interrogating fragmentation patterns for a cysteine-reactive chemoproteomic probe, RNA-crosslinked peptides, sialic acid-containing glycopeptides, and ADP-ribosylated peptides. We also analyze the interactions between a diagnostic ion's intensity and its statistical properties. This method has been incorporated into the open-search annotation tool PTM-Shepherd and the FragPipe computational platform.
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Affiliation(s)
- Daniel J Geiszler
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
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42
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Sun W, Zhang Q, Zhang X, Tran NH, Ziaur Rahman M, Chen Z, Peng C, Ma J, Li M, Xin L, Shan B. Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics. Nat Commun 2023; 14:4046. [PMID: 37422459 PMCID: PMC10329677 DOI: 10.1038/s41467-023-39699-5] [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: 09/26/2022] [Accepted: 06/19/2023] [Indexed: 07/10/2023] Open
Abstract
Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact glycopeptides from mass spectrometry data. GlycanFinder integrates peptide-based and glycan-based search strategies to address the challenge of complex fragmentation of glycopeptides. A deep learning model is designed to capture glycan tree structures and their fragment ions for de novo sequencing of glycans that do not exist in the database. We performed extensive analyses to validate the false discovery rates (FDRs) at both peptide and glycan levels and to evaluate GlycanFinder based on comprehensive benchmarks from previous community-based studies. Our results show that GlycanFinder achieved comparable performance to other leading glycoproteomics softwares in terms of both FDR control and the number of identifications. Moreover, GlycanFinder was also able to identify glycopeptides not found in existing databases. Finally, we conducted a mass spectrometry experiment for antibody N-linked glycosylation profiling that could distinguish isomeric peptides and glycans in four immunoglobulin G subclasses, which had been a challenging problem to previous studies.
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Affiliation(s)
- Weiping Sun
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Qianqiu Zhang
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada
| | - Xiyue Zhang
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Ngoc Hieu Tran
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada
| | - M Ziaur Rahman
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Zheng Chen
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Chao Peng
- BaizhenBio Inc., Wuhan, China
- Wuhan BioBank, Wuhan, China
| | - Jun Ma
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Ming Li
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada.
- Henan Academy of Sciences, Zhengzhou, Henan, China.
| | - Lei Xin
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada.
| | - Baozhen Shan
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada.
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43
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Xu S, Wu R. Glycobiology and proteomics: has mass spectrometry moved the field forward? Expert Rev Proteomics 2023; 20:303-307. [PMID: 37667879 PMCID: PMC10841282 DOI: 10.1080/14789450.2023.2255748] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 07/26/2023] [Indexed: 09/06/2023]
Affiliation(s)
- Senhan Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Ronghu Wu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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44
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Silva MLS. Capitalizing glycomic changes for improved biomarker-based cancer diagnostics. EXPLORATION OF TARGETED ANTI-TUMOR THERAPY 2023; 4:366-395. [PMID: 37455827 PMCID: PMC10344901 DOI: 10.37349/etat.2023.00140] [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: 10/10/2022] [Accepted: 02/24/2023] [Indexed: 07/18/2023] Open
Abstract
Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.
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Affiliation(s)
- Maria Luísa S. Silva
- Unidade de Aprendizagem ao Longo da Vida, Universidade Aberta, 1269-001 Lisboa, Portugal
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45
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Dhingra A, Schaeffer Z, Majewska Nepomuceno NI, Au J, Ahn J. A MATLAB-based app to improve LC-MS/MS data analysis for N-linked glycan peak identification. BMC Bioinformatics 2023; 24:259. [PMID: 37330473 DOI: 10.1186/s12859-023-05346-5] [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: 11/18/2022] [Accepted: 05/18/2023] [Indexed: 06/19/2023] Open
Abstract
BACKGROUND Glycosylation is an important modification to proteins that plays a significant role in biological processes. Glycan structures are characterized by liquid chromatography (LC) combined with mass spectrometry (MS), but data interpretation of LC/MS and MS/MS data can be time-consuming and arduous when analyzed manually. Most of glycan analysis requires dedicated glycobioinformatics tools to process MS data, identify glycan structure, and display the results. However, software tools currently available are either too costly or heavily focused on academic applications, limiting their use within the biopharmaceutical industry for implementing the standardized LC/MS glycan analysis in high-throughput manner. Additionally, few tools provide the capability to generate report-ready annotated MS/MS glycan spectra. RESULTS Here, we present a MATLAB-based app, GlyKAn AZ, which can automate data processing, glycan identification, and customizable result displays in a streamlined workflow. MS1 and MS2 mass search algorithms along with glycan databases were developed to confirm the fluorescent labeled N-linked glycan species based on accurate mass. A user-friendly graphical user interface (GUI) streamlines the data analysis process, making it easy to implement the software tool in biopharmaceutical analytical laboratories. The databases provided with the app can be expanded through the Fragment Generator functionality which automatically identifies fragmentation patterns for new glycans. The GlyKAn AZ app can automatically annotate the MS/MS spectra, yet this data display feature remains flexible and customizable by users, saving analysts' time in generating individual report-ready spectra figures. This app accepts both OrbiTrap and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS data and was successfully validated by identifying all glycan species that were previously identified manually. CONCLUSIONS The GlyKAn AZ app was developed to expedite glycan analysis while maintaining a high level of accuracy in positive identifications. The app's customizable user inputs, polished figures and tables, and unique calculated outputs set it apart from similar software and greatly improve the current manual analysis workflow. Overall, this app serves as a tool for streamlining glycan identification for both academic and industrial needs.
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Affiliation(s)
- Ashna Dhingra
- Bioprocess Technologies and Engineering, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Zayla Schaeffer
- Bioprocess Technologies and Engineering, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA.
| | - Natalia I Majewska Nepomuceno
- Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jennifer Au
- Cell Culture and Fermentation Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Joomi Ahn
- Analytical Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
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46
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Bedran G, Polasky DA, Hsiao Y, Yu F, da Veiga Leprevost F, Alfaro JA, Cieslik M, Nesvizhskii AI. Unraveling the glycosylated immunopeptidome with HLA-Glyco. Nat Commun 2023; 14:3461. [PMID: 37308510 PMCID: PMC10258777 DOI: 10.1038/s41467-023-39270-2] [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: 11/07/2022] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
Recent interest in targeted therapies has been sparked by the study of MHC-associated peptides (MAPs) that undergo post-translational modifications (PTMs), particularly glycosylation. In this study, we introduce a fast computational workflow that merges the MSFragger-Glyco search algorithm with a false discovery rate control for glycopeptide analysis from mass spectrometry-based immunopeptidome data. By analyzing eight large-scale publicly available studies, we find that glycosylated MAPs are predominantly presented by MHC class II. Here, we present HLA-Glyco, a comprehensive resource containing over 3,400 human leukocyte antigen (HLA) class II N-glycopeptides from 1,049 distinct protein glycosylation sites. This resource provides valuable insights, including high levels of truncated glycans, conserved HLA-binding cores, and differences in glycosylation positional specificity between HLA allele groups. We integrate the workflow within the FragPipe computational platform and provide HLA-Glyco as a free web resource. Overall, our work provides a valuable tool and resource to aid the nascent field of glyco-immunopeptidomics.
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Affiliation(s)
- Georges Bedran
- International Centre for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Yi Hsiao
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | | | - Javier A Alfaro
- International Centre for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Marcin Cieslik
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
- Michigan Center for Translational Pathology, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA.
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47
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Xie X, Kong S, Cao W. Targeting protein glycosylation to regulate inflammation in the respiratory tract: novel diagnostic and therapeutic candidates for chronic respiratory diseases. Front Immunol 2023; 14:1168023. [PMID: 37256139 PMCID: PMC10225578 DOI: 10.3389/fimmu.2023.1168023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 05/02/2023] [Indexed: 06/01/2023] Open
Abstract
Protein glycosylation is a widespread posttranslational modification that can impact the function of proteins. Dysregulated protein glycosylation has been linked to several diseases, including chronic respiratory diseases (CRDs). CRDs pose a significant public health threat globally, affecting the airways and other lung structures. Emerging researches suggest that glycosylation plays a significant role in regulating inflammation associated with CRDs. This review offers an overview of the abnormal glycoenzyme activity and corresponding glycosylation changes involved in various CRDs, including chronic obstructive pulmonary disease, asthma, cystic fibrosis, idiopathic pulmonary fibrosis, pulmonary arterial hypertension, non-cystic fibrosis bronchiectasis, and lung cancer. Additionally, this review summarizes recent advances in glycomics and glycoproteomics-based protein glycosylation analysis of CRDs. The potential of glycoenzymes and glycoproteins for clinical use in the diagnosis and treatment of CRDs is also discussed.
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Affiliation(s)
- Xiaofeng Xie
- Shanghai Fifth People’s Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Siyuan Kong
- Shanghai Fifth People’s Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Weiqian Cao
- Shanghai Fifth People’s Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China
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48
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Toul M, Slonkova V, Mican J, Urminsky A, Tomkova M, Sedlak E, Bednar D, Damborsky J, Hernychova L, Prokop Z. Identification, characterization, and engineering of glycosylation in thrombolyticsa. Biotechnol Adv 2023; 66:108174. [PMID: 37182613 DOI: 10.1016/j.biotechadv.2023.108174] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/09/2023] [Accepted: 05/09/2023] [Indexed: 05/16/2023]
Abstract
Cardiovascular diseases, such as myocardial infarction, ischemic stroke, and pulmonary embolism, are the most common causes of disability and death worldwide. Blood clot hydrolysis by thrombolytic enzymes and thrombectomy are key clinical interventions. The most widely used thrombolytic enzyme is alteplase, which has been used in clinical practice since 1986. Another clinically used thrombolytic protein is tenecteplase, which has modified epitopes and engineered glycosylation sites, suggesting that carbohydrate modification in thrombolytic enzymes is a viable strategy for their improvement. This comprehensive review summarizes current knowledge on computational and experimental identification of glycosylation sites and glycan identity, together with methods used for their reengineering. Practical examples from previous studies focus on modification of glycosylations in thrombolytics, e.g., alteplase, tenecteplase, reteplase, urokinase, saruplase, and desmoteplase. Collected clinical data on these glycoproteins demonstrate the great potential of this engineering strategy. Outstanding combinatorics originating from multiple glycosylation sites and the vast variety of covalently attached glycan species can be addressed by directed evolution or rational design. Directed evolution pipelines would benefit from more efficient cell-free expression and high-throughput screening assays, while rational design must employ structure prediction by machine learning and in silico characterization by supercomputing. Perspectives on challenges and opportunities for improvement of thrombolytic enzymes by engineering and evolution of protein glycosylation are provided.
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Affiliation(s)
- Martin Toul
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Veronika Slonkova
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jan Mican
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Adam Urminsky
- Research Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Zluty kopec 7, 656 53 Brno, Czech Republic
| | - Maria Tomkova
- Center for Interdisciplinary Biosciences, P. J. Safarik University in Kosice, Jesenna 5, 04154 Kosice, Slovakia
| | - Erik Sedlak
- Center for Interdisciplinary Biosciences, P. J. Safarik University in Kosice, Jesenna 5, 04154 Kosice, Slovakia
| | - David Bednar
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Lenka Hernychova
- Research Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Zluty kopec 7, 656 53 Brno, Czech Republic.
| | - Zbynek Prokop
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic.
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Li X, Du Y, Chen X, Liu C. Emerging roles of O-glycosylation in regulating protein aggregation, phase separation, and functions. Curr Opin Chem Biol 2023; 75:102314. [PMID: 37156204 DOI: 10.1016/j.cbpa.2023.102314] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/28/2023] [Accepted: 04/02/2023] [Indexed: 05/10/2023]
Abstract
Protein O-glycosylation is widely identified in various proteins involved in diverse biological processes. Recent studies have demonstrated that O-glycosylation plays crucial and multifaceted roles in modulating protein amyloid aggregation and liquid-liquid phase separation (LLPS) under physiological conditions. Dysregulation of these processes is closely associated with human diseases such as neurodegenerative diseases (NDs) and cancers. In this review, we first summarize the distinct roles of O-glycosylation in regulating pathological aggregation of different amyloid proteins related to NDs and elaborate the underlying mechanisms of how O-glycosylation modulates protein aggregation kinetics, induces new aggregated structures, and mediates the pathogenesis of amyloid aggregates under diseased conditions. Furthermore, we introduce recent discoveries on O-GlcNAc-mediated regulation of synaptic LLPS and phase separation potency of low-complexity domain-enriched proteins. Finally, we identify challenges in future research and highlight the potential for developing new therapeutic strategies of NDs by targeting protein O-glycosylation.
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Affiliation(s)
- Xiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yifei Du
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China; Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xing Chen
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China; Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; Synthetic and Functional Biomolecules Center, Peking University, Beijing, China; Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, China.
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China; State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China.
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50
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Wang Z, Fang Z, Liu L, Zhu H, Wang Y, Zhao C, Guo Z, Qin H, Nie Y, Liang X, Dong M, Ye M. Development of an Integrated Platform for the Simultaneous Enrichment and Characterization of N- and O-Linked Intact Glycopeptides. Anal Chem 2023; 95:7448-7457. [PMID: 37146305 DOI: 10.1021/acs.analchem.2c04305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Both N-linked glycosylation and O-linked glycosylation play essential roles in the onset and progression of various diseases including cancer, and N-/O-linked site-specific glycans have been proven to be promising biomarkers for the discrimination of cancer. However, the micro-heterogeneity and low abundance nature of N-/O-linked glycosylation, as well as the time-consuming and tedious procedures for the enrichment of O-linked intact glycopeptides, pose great challenges for their efficient and accurate characterization. In this study, we developed an integrated platform for the simultaneous enrichment and characterization of N- and O-linked intact glycopeptides from the same serum sample. By fine-tuning the experimental conditions, we demonstrated that this platform allowed the selective separation of N- and O-linked intact glycopeptides into two fractions, with 85.1% O-linked intact glycopeptides presented in the first fraction and 93.4% N-linked intact glycopeptides presented in the second fraction. Determined with high reproducibility, this platform was further applied to the differential analysis of serum samples of gastric cancer and health control, which revealed 17 and 181 significantly changed O-linked and N-linked intact glycopeptides. Interestingly, five glycoproteins containing both significant regulation of N- and O-glycosylation were observed, hinting potential co-regulation of different types of glycosylation during tumor progress. In summary, this integrated platform opened a potentially useful avenue for the global analysis of protein glycosylation and can serve as a useful tool for the characterization of N-/O-linked intact glycopeptides at the proteomics scale.
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Affiliation(s)
- Zhongyu Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zheng Fang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luyao Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - He Zhu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yan Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
| | - Changrui Zhao
- Liaoning Key Laboratory of Molecular Recognition and Imaging, School of Bioengineering, Dalian University of Technology, Dalian, Liaoning 116023, China
| | - Zhimou Guo
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
| | - Hongqiang Qin
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
| | - Yongzhan Nie
- State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an 710032, China
| | - Xinmiao Liang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
| | - Mingming Dong
- Liaoning Key Laboratory of Molecular Recognition and Imaging, School of Bioengineering, Dalian University of Technology, Dalian, Liaoning 116023, China
| | - Mingliang Ye
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, Liaoning 116023, China
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