Literature DB >> 33166117

Utility of Ion-Mobility Spectrometry for Deducing Branching of Multiply Charged Glycans and Glycopeptides in a High-Throughput Positive ion LC-FLR-IMS-MS Workflow.

Edward G Pallister1,2, Matthew S F Choo1, Ian Walsh1, Jien Nee Tai1, Shi Jie Tay1, Yuan Sheng Yang1, Say Kong Ng1, Pauline M Rudd1, Sabine L Flitsch2, Terry Nguyen-Khuong1.   

Abstract

High-throughput glycan analysis has become an important part of biopharmaceutical production and quality control. However, it is still a significant challenge in the field of glycomics to easily deduce isomeric glycan structures, especially in a high-throughput manner. Ion mobility spectrometry (IMS) is an excellent tool for differentiating isomeric glycan structures. However, demonstrations of the utility of IMS in high-throughput workflows such as liquid chromatography-fluorescence-mass spectrometry (LC-FLR-MS) workflows have been limited with only a small amount of collision cross section (CCS) data available. In particular, IMS data of glycan fragments obtained in positive ion mode are limited in comparison to those obtained in negative ion mode despite positive ion mode being widely used for glycomics. Here, we describe IMS TWCCSN2 data obtained from a high-throughput LC-FLR-IMS-MS workflow in positive ion mode. We obtained IMS data from a selection of RapiFluor-MS (RFMS) labeled N-glycans and also glycopeptides. We describe how IMS is able to distinguish isomeric N-glycans and glycopeptides using both intact IMS and fragment-based IMS glycan sequencing experiments in positive ion mode, without significantly altering the high-throughput nature of the analysis. For the first time, we were able to successfully use IMS in positive ion mode to determine the branching of isomeric glycopeptides and RFMS labeled glycans. Further, we highlight that IMS glycan sequencing of fragments obtained from RFMS labeled glycans was similar to that of glycopeptides. Finally, we show that the IMS glycan sequencing approach can highlight shared structural features of nonisomeric glycans in a high-throughput LC-FLR-IMS-MS workflow.

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Year:  2020        PMID: 33166117     DOI: 10.1021/acs.analchem.0c01954

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  8 in total

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2.  An Integrative Glycomic Approach for Quantitative Meat Species Profiling.

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3.  Semi-Automated Glycoproteomic Data Analysis of LC-MS Data Using GlycopeptideGraphMS in Process Development of Monoclonal Antibody Biologics.

Authors:  Kuin Tian Pang; Shi Jie Tay; Corrine Wan; Ian Walsh; Matthew S F Choo; Yuan Sheng Yang; Andre Choo; Ying Swan Ho; Terry Nguyen-Khuong
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4.  Bisecting Lewis X in Hybrid-Type N-Glycans of Human Brain Revealed by Deep Structural Glycomics.

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Journal:  Anal Chem       Date:  2021-11-01       Impact factor: 8.008

5.  Identification of N-glycan positional isomers by combining IMS and vibrational fingerprinting of structurally determinant CID fragments.

Authors:  Priyanka Bansal; Ahmed Ben Faleh; Stephan Warnke; Thomas R Rizzo
Journal:  Analyst       Date:  2022-02-14       Impact factor: 4.616

6.  Determination of Sialic Acid Isomers from Released N-Glycans Using Ion Mobility Spectrometry.

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Review 7.  MS-based glycomics and glycoproteomics methods enabling isomeric characterization.

Authors:  Wenjing Peng; Cristian D Gutierrez Reyes; Sakshi Gautam; Aiying Yu; Byeong Gwan Cho; Mona Goli; Kaitlyn Donohoo; Stefania Mondello; Firas Kobeissy; Yehia Mechref
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8.  A new approach for identifying positional isomers of glycans cleaved from monoclonal antibodies.

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Journal:  Analyst       Date:  2021-07-26       Impact factor: 4.616

  8 in total

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