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1. Plasma glycoproteomics delivers high-specificity disease biomarkers by detecting site-specific glycosylation abnormalities

Author

Hans J.C.T. Wessels, Purva Kulkarni, Maurice van Dael, Anouk Suppers, Esther Willems, Fokje Zijlstra, Else Kragt, Jolein Gloerich, Pierre-Olivier Schmit, Stuart Pengelley, Kristina Marx, Alain J. van Gool, and Dirk J. Lefeber

Subjects
Glycosylation, Glycoproteomics, Blood plasma, Congenital disorders of glycosylation, Clinical applications, Medicine (General), R5-920, Science (General), Q1-390
Abstract

Introduction: The human plasma glycoproteome holds enormous potential to identify personalized biomarkers for diagnostics. Glycoproteomics has matured into a technology for plasma N-glycoproteome analysis but further evolution towards clinical applications depends on the clinical validity and understanding of protein- and site-specific glycosylation changes in disease. Objectives: Here, we exploited the uniqueness of a patient cohort of genetic defects in well-defined glycosylation pathways to assess the clinical applicability of plasma N-glycoproteomics. Methods: Comparative glycoproteomics was performed of blood plasma from 40 controls and 74 patients with 13 different genetic diseases that impact the protein N-glycosylation pathway. Baseline glycosylation in healthy individuals was compared to reference glycome and intact transferrin protein mass spectrometry data. Use of glycoproteomics data for biomarker discovery and sample stratification was evaluated by multivariate chemometrics and supervised machine learning. Clinical relevance of site-specific glycosylation changes were evaluated in the context of genetic defects that lead to distinct accumulation or loss of specific glycans. Integrated analysis of site-specific glycoproteome changes in disease was performed using chord diagrams and correlated with intact transferrin protein mass spectrometry data. Results: Glycoproteomics identified 191 unique glycoforms from 58 unique peptide sequences of 34 plasma glycoproteins that span over 3 magnitudes of abundance in plasma. Chemometrics identified high-specificity biomarker signatures for each of the individual genetic defects with better stratification performance than the current diagnostic standard method. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and protein-intrinsic factors. Conclusion: Our work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the glycobiological mechanisms underlying human disease.

Published
2024
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2. NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies

Author

Miyako Nakano, Alena Wiegandt, Yunli Hu, Viv Lindo, Paulina A. Urbanowicz, Zsuzsanna Lakos, Cassie Caron, Song Klapoetke, Niels Christian Reichardt, Niclas Chiang Tan, Sandra Maier, Rene Hennig, Marton Szigeti, Ju Yeon Lee, Ying Qing Yu, Gregory O. Staples, Sachin Patil, Jolanta Jaworek, Waltraud Evers, Benjamin G. Kremkow, Youngsuk Seo, Kathirvel Alagesan, Yuetian Chen, Gordan Lauc, David L. Duewer, Yang Yang, Daniele Menard, Hyun Joo An, Tim Kelly, Stephen E. Stein, Joseph W. Leone, Anja Wiechmann, Ravi Amunugama, Peng George Wang, Clemens Grunwald-Grube, Maria Lorna A. De Leoz, Göran Larson, Rob Haselberg, Samanta Cajic, Stephanie A. Archer-Hartmann, Maja Pučić-Baković, Edward D. Bodnar, Pauline M. Rudd, Anja Resemann, Daniel Kolarich, Akira Harazono, Jeffrey S. Rohrer, Juan Echevarria Ruiz, Stuart Pengelley, Jong Shin Yoo, Arun V. Everest-Dass, Nicolle H. Packer, Steven W. Mast, William R. Alley, Erika Lattová, Anne Zeck, Corné J.M. Stroop, Radoslaw P. Kozak, Chun Shao, Alain Beck, Joseph Zaia, Erdmann Rapp, Lily Liu, Jennie Truong, Yaojun Wang, Christopher W. Cairo, Roisin O'Flaherty, Radka Saldova, Kudrat Goswami, Emy Komatsu, Jessica Örnros, Taiki Sugiyama, Prachi Bhoskar, Pralima Pradhan, Carlito B. Lebrilla, András Guttman, Christine Merle, Brian Kasper, Oscar G. Potter, Soo Kyung Suh, Li Phing Liew, Ranjan Chakrabarti, Terry D. Cyr, Sohei Funaoka, Masaaki Toyoda, Pui King Amy Leung, Toyin Kasali, Jerko Štambuk, Yanming An, Wolfgang Jabs, Bernd Meyer, Chunxia Zou, John F. Cipollo, Sa Rang Kim, Aaron Shafer, Randy M. Whittal, Jichao Kang, Albert J. R. Heck, Yehia Mechref, Hoi Kei Yau, Guinevere S. M. Lageveen-Kammeijer, Shiwei Sun, Kenichiro Furuki, Richard B. Jones, Béla Reiz, Niclas G. Karlsson, Mohammedazam Lahori, Xu Li, Barbara Adamczyk, Rui Cao, Lauren Wu, Koichi Kato, Detlev Suckau, Paweł Link-Lenczowski, Kelvin H. Lee, Xiaomin Song, Noortje de Haan, Ruth Frenkel, Adam Fung, Friedrich Altmann, Manfred Wuhrer, David Falck, Andreas Bock, Paula Magnelli, Brian Gau, Sachiko Kondo, Robert J. Emery, Chunsheng Jin, Louise Royle, David C. Muddiman, Hélène Perreault, John W. Froehlich, Disha Dadke, Peiqing Zhang, Lara K. Mahal, Takashi Nishikaze, Andrew Saati, Chuncui Huang, Hui Zhang, Carina Sihlbom, Parastoo Azadi, Jonas Nilsson, Yaming Liu, Yannis-Nicolas François, Nassur Said, Jin Young Kim, C. T. Yuen, Shuang Yang, Emmanuelle Leize-Wagner, David Harvey, Xiaofeng Shi, Yan Li, Hirokazu Yagi, Zoran Sosic, Elizabeth M. Hecht, Hua Yuan, Marybeth Creskey, Hyun Kyoung Lee, Sadanori Sekiya, Peter de Vreugd, Len Bell, Sam Tep, BioAnalytical Chemistry, AIMMS, Department of Plant and Microbial Biology, University of California, Laboratory of Infrared Material and Devices, Ningbo University (NBU), University of Natural Resources and Life Sciences (BOKU), Bruker Daltonik GmbH, Bruker Daltonik, Centre d'Immunologie Pierre Fabre, Xinjiang Agriculture University, Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III [Madrid] (ISC)-ministerio de ciencia e innovacion, Complex Carbohydrate Research Center, University of Georgia [USA], GENOS, Universität Duisburg-Essen [Essen], Max Planck Institute for Dynamics of Complex Technical Systems, Max-Planck-Gesellschaft, Section de mathématiques [Genève], Université de Genève (UNIGE), Department of Computer Science [York] (CS-YORK), University of York [York, UK], State Key Laboratory of Hybrid Rice, Department of Genetics, College of Life Sciences, Wuhan University, LeidenUniversity Medical Center, University College Dublin [Dublin] (UCD), Texas A&M University System, College of Engineering and Computer Science, Australian National University (ANU), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), University of Edinburgh, University of Alberta, Department of Biological Sciences, Mass Spectrometry Facility, University of Alberta-Department of Chemistry, Volvo Car Corporation, Centre for Research in Intelligent Systems, Monash University [Clayton], Department of Chemistry [Winnipeg, MB, Canada], University of Manitoba [Winnipeg], Department of Chemistry [Winnipeg, Manitoba, Canada], Université de Strasbourg (UNISTRA), Laboratoire de synthèses métallo-induites, Dynamique et structure moléculaire par spectrométrie de masse (LDSM2), School of Mechanics and Engineering [Chengdu], Southwest Jiaotong University (SWJTU), School of Management and Economics [University of Electronic Science and Technology of China], and University of Electronic Science and Technology of China (UESTC)

Subjects
Proteomics, PROTEIN, fluerescence, Biochemistry, reference antibody, THERAPEUTIC ANTIBODIES, Biopharmaceutics, Analytical Chemistry, chemistry.chemical_compound, Biological sciences, Glycomics, NISTaAb, Analysis method, ComputingMilieux_MISCELLANEOUS, glycoproteins, mass spectrometry, chemistry.chemical_classification, 0303 health sciences, glycan, interlaboratory study, 030302 biochemistry & molecular biology, Glycopeptides, Antibodies, Monoclonal, 3. Good health, glycomics, fluorescence, glycosylation, glycopeptide, NISTmAb, lipids (amino acids, peptides, and proteins), Protein glycosylation, Glycan, Glycosylation, QUANTITATION, medicine.drug_class, Computational biology, Biology, Monoclonal antibody, 03 medical and health sciences, GLYCOMIC ANALYSIS, SDG 3 - Good Health and Well-being, Polysaccharides, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Report, medicine, Humans, LC-MS/MS, Molecular Biology, 030304 developmental biology, Biological Products, IDENTIFICATION, MASS-SPECTROMETRY, PROFILES, QUANTIFICATION, carbohydrates (lipids), chemistry, biology.protein, Laboratories, Glycoprotein, Protein Processing, Post-Translational
Abstract

A broad-based interlaboratory study of glycosylation profiles of a reference and modified IgG antibody involving 103 reports from 76 laboratories., Graphical Abstract Highlights A broad-based interlaboratory study of the glycosylation of a reference antibody: NISTmAb. 103 reports were received from 76 diverse laboratories worldwide. Analysis involved two samples, the NISTmAb and an enzymatically modified sample, enabling within-lab separation of random and systematic errors using the “Youden two-sample” method. Consensus values were derived and similar performance across all experimental methods was noted., Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods.

Published
2020
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3. Interlaboratory study for characterizing monoclonal antibodies by top-down and middle-down mass spectrometry

Author

Sam Hughes, Nicolas L. Young, David Clarke, Frank Sobott, Anja Resemann, Kristina Srzentić, Kim F. Haselmann, Detlev Suckau, Dina L. Bai, Young Ah Goo, Christian Malosse, Mathieu Dupré, Sylvester M. Greer, Neil R. Quebbemann, Ziqing Lin, Jared B. Shaw, Alain Beck, Yury O. Tsybin, Stuart Pengelley, Timothy K. Toby, Lidong He, Paul O. Danis, Henrique S. Seckler, Robert Anthony D’Ippolito, Natalia Gasilova, Jeffrey N. Agar, Donald F. Hunt, Jennifer S. Brodbelt, Matthew V. Holt, Simone Nicolardi, Joseph A. Loo, Yuri E. M. van der Burgt, Nicholas D. Schmitt, Laure Menin, Robert J. Millikin, Ljiljana Paša-Tolić, David R. Goodlett, Mowei Zhou, Joshua D. Hinkle, Michael R. Shortreed, Christopher L. Hendrickson, Wendy Sandoval, Richa Sarin, Jeffrey Shabanowitz, Alan G. Marshall, Anton N. Kozhinov, Neil L. Kelleher, Chad R. Weisbrod, Lissa C. Anderson, Julia Chamot-Rooke, Yunqiu Chen, John R. Yates, Luca Fornelli, Konstantin O. Nagornov, Lloyd M. Smith, Sneha Chatterjee, Ying Ge, Sung Hwan Yoon, Jolene K. Diedrich, Norelle C. Wildburger, Centre de Recherche Pierre Fabre (Centre de R&D Pierre Fabre), PIERRE FABRE, Institut Pasteur [Paris], and Institut Pasteur [Paris] (IP)

Subjects
Proteomics, medicine.drug_class, [SDV]Life Sciences [q-bio], Computational biology, 010402 general chemistry, Tandem mass spectrometry, Monoclonal antibody, Mass spectrometry, 01 natural sciences, Article, Antibodies, Mass Spectrometry, FTMS, Analytical Chemistry, Mice, Medicinal and Biomolecular Chemistry, Structural Biology, Monoclonal, intact mass measurement, tandem mass spectrometry, medicine, MS/MS, Animals, Humans, Biology, Spectroscopy, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], Chemistry, 010401 analytical chemistry, Therapeutic protein, Antibodies, Monoclonal, Complementarity Determining Regions, 0104 chemical sciences, 3. Good health, Fourier transform mass spectrometry, Ion dissociation, glycoform, Therapeutic antibody, Biotechnology, Physical Chemistry (incl. Structural)
Abstract

International audience; The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.

Published
2020
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4. The Art of Destruction: Optimizing Collision Energies in Quadrupole-Time of Flight (Q-TOF) Instruments for Glycopeptide-Based Glycoproteomics

Author

Ulrike Schweiger-Hufnagel, Peter H. Seeberger, Wolfgang Jabs, Manfred Wuhrer, Daniel Kolarich, Stuart Pengelley, Hannes Hinneburg, Daniel Varón Silva, and Kathrin Stavenhagen

Subjects
0301 basic medicine, Proteomics, Glycan, Spectrometry, Mass, Electrospray Ionization, Glycosylation, Collision-induced dissociation, Immunoglobulins, Tandem mass spectrometry, Mass spectrometry, Glycopeptide, 01 natural sciences, 03 medical and health sciences, chemistry.chemical_compound, Fragmentation (mass spectrometry), Structural Biology, Tandem Mass Spectrometry, Immunoglobulin, Animals, Humans, Amino Acid Sequence, Fetuins, Spectroscopy, Chromatography, biology, 010401 analytical chemistry, Glycopeptides, Collision energy stepping CID, Glycoproteomics, 0104 chemical sciences, O-glycan, 030104 developmental biology, chemistry, Carbohydrate Sequence, N-glycan, biology.protein, Cattle, Synthetic glycopeptides, Biological system, Research Article, Q-TOF
Abstract

In-depth site-specific investigations of protein glycosylation are the basis for understanding the biological function of glycoproteins. Mass spectrometry-based N- and O-glycopeptide analyses enable determination of the glycosylation site, site occupancy, as well as glycan varieties present on a particular site. However, the depth of information is highly dependent on the applied analytical tools, including glycopeptide fragmentation regimes and automated data analysis. Here, we used a small set of synthetic disialylated, biantennary N-glycopeptides to systematically tune Q-TOF instrument parameters towards optimal energy stepping collision induced dissociation (CID) of glycopeptides. A linear dependency of m/z-ratio and optimal fragmentation energy was found, showing that with increasing m/z-ratio, more energy is required for glycopeptide fragmentation. Based on these optimized fragmentation parameters, a method combining lower- and higher-energy CID was developed, allowing the online acquisition of glycan and peptide-specific fragments within a single tandem MS experiment. We validated this method analyzing a set of human immunoglobulins (IgA1+2, sIgA, IgG1+2, IgE, IgD, IgM) as well as bovine fetuin. These optimized fragmentation parameters also enabled software-assisted glycopeptide assignment of both N- and O-glycopeptides including information about the most abundant glycan compositions, peptide sequence and putative structures. Twenty-six out of 30 N-glycopeptides and four out of five O-glycopeptides carrying >110 different glycoforms could be identified by this optimized LC-ESI tandem MS method with minimal user input. The Q-TOF based glycopeptide analysis platform presented here opens the way to a range of different applications in glycoproteomics research as well as biopharmaceutical development and quality control. Graphical Abstract ᅟ Electronic supplementary material The online version of this article (doi:10.1007/s13361-015-1308-6) contains supplementary material, which is available to authorized users.

Published
2016

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