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The NJ Mass Spectrometry Discussion Group is pleased to announce our April 25, 2023 Meeting — Online!
NJ MSDG is the second largest mass spectrometry professional association in the nation behind ASMS, with over 1,100 members in the tristate area.
Date:.....Tuesday April 25, 2023
Time:.....7:00 PM | (UTC-05:00) Eastern Time (US & Canada)
Join:.....[ below ]
Speaker 1: Ron Orlando, PhD, Complex Carbohydrate Research Center; Department of Biochemistry & Molecular Biology and Chemistry; University of Georgia
“HILIC/MS – It’s not just for Glycans. Identification of Glycopeptides and Modified Peptides with the Combination of MS and HILIC Retention Modeling”
Abstract:Speaker 2: Heidi Vitrac, Sr. Market Development Scientist, MOBILion Systems
Abstract: Many of the chemical modifications that play a role in biological processes and protein aging often change the hydrophilicity of the modified amino acid’s side chain. These alterations can include the attachment of a single (or multiple) monosaccharides, oxidation of methionine, the deamidation of asparagine, and isomerization of aspartic acid, among others. Using conventional reverse-phase approaches, the peptides with and without these modifications often do not exhibit sufficient separation from one another, or when these can be chromatographically resolved the shift in retention is easily predictable. Changes in hydrophilicity directly alter a peptide’s retention on hydrophilic interaction liquid chromatography (HILIC) columns.
We have created a HILIC model that can predict the retention of peptides with various modifications. We have shown the ability to chromatographically resolve and quantitate products of deamidation, isomerization, oxidation, O-GlcNAcylation, and glycation. We have derived retention coefficients for these modified amino acids, and have incorporated them into a model that predicts peptide retention on HILIC columns.
The analysis of an extensive range of procainamide tagged N-linked glycans has led to a HILIC retention model for this class of biomolecule. The N-glycan model was combined with the peptide model, described above, to produce a prediction model for glycopeptides. The efficacy of the combined model was evaluated by comparing experimental data obtained via LC-MS analysis of human serum IgGs to those calculated with the model.
We feel that the unified chromatographic model (amino acids, modified amino acids, N-linked glycans) will facilitate the identification and quantification of peptides containing these modifications.
“Unraveling the Released N-Glycan Isomerome Complexity by Implementing High-Resolution Ion Mobility (HRIM) in the HILIC-MS Workflow”
Abstract: The N-linked glycan moieties attached to therapeutic monoclonal antibodies (mAbs) can affect protein stability, bioactivity, and immunogenicity. Simple, biantennary N-linked glycan structures are readily assessed using simple fluorophore derivatization, online liquid chromatography, and fluorescence detection. However, traditional mAb-released N-linked glycan analysis results in a 15-60% ambiguity rate based on the inability to resolve isomers and reporting of compositions only. Furthermore, more complex protein biopharmaceuticals with glycosylation populations, such as Erythropoietin, highlight the need for tighter requirements for carbohydrate analysis, such as determining the antennal composition and elucidating of positional isomers. Here, we report that HRIM implementation in the workflow improves confidence in detecting and identifying N-linked glycan structures and isomers, while reducing data acquisition time.
InstantPC-labeled N-linked glycan biantennary standards were analyzed using a combination of flow injection analysis and hydrophilic interaction liquid chromatography (HILIC) separation. Data was acquired on an HRIM MOBIE™ instrument (MOBILion Systems) coupled to a 6545XT QTOF (Agilent Technologies). Accurate mass, isotope spacing, ion mobility arrival time distribution, and Collision Cross Section (CCS) determination were used to identify each N-linked glycan. Each alpha- and beta-linked N-linked glycan isomer structure was verified by analyzing individual standards. Data processing, analysis, relative quantification, and visualization were achieved using HRIM Data Processor, PNNL Preprocessor, and Protein Metrics Byos® Software.
First, flow injection analysis of 28 InstantPC-labeled N-linked glycan compositions (of which, 12 have isomeric linkages) was conducted to determine the HRIM-MS profiles of each N-glycan. For each labeled N-linked glycan, accurate mass, isotope spacing, ion mobility arrival time distribution, and Collision Cross Section (CCS) values were determined with a minimum of triplicate measurements. N-linked glycan detection, identity validation, and relative quantitation were conducted, generating an N-linked glycan feature library used in later HILIC-HRIM-MS analytical workflows. We demonstrate that HRIM-MS allows for the separation, confident identification, and quantification of all 28 N-linked glycan species. Further, all 12 N-linked glycan isomers could be resolved into multiple ion mobility peaks in the gas phase, without any LC separation. Rapid N-linked glycan profiling was further demonstrated by analyzing a human IgG-released InstantPC-labeled N-linked glycan library. Altogether, our flow injection results demonstrate that HRIM-MS offers excellent potential for rapidly and confidently revealing complex glycoform profiles.
Second, we implemented HRIM in the traditional HILIC-MS analytical workflow for released N-linked glycans, intending to test the complementarity of HILIC and HRIM separation. Varying HILIC run times (60-, and 15-minute gradients) were tested to assess the ability of HRIM to resolve N-linked glycans in the gas phase while HILIC separation times were gradually reduced. All three HILIC gradients resulted in comparable relative N-linked glycan species coverage and isomer separation, with consistent and reproducible relative quantitation based on extracted ion mobiligrams. Our results demonstrate that HRIM-MS provides high-quality and rapid N-linked glycan feature identification (including isomeric separation) and relative quantitation. Leveraging accurate and reproducible CCS determination, adding HRIM to a traditional LC-MS method provides a solution for confidently fingerprinting glycosylation profiles in biotherapeutics, enabling a greater depth in N-linked glycan feature detection or increased analytical throughput.
Three bullet points about the talk:
- Traditional mAb-released N-glycan analysis results in a 15-60% ambiguity rate based on the inability to resolve isomers and reporting of compositions only.
- HRIM-MS allows for the separation, confident identification, and quantification of released N-glycan species, including isomer resolution, without any LC separation.
- Leveraging accurate and reproducible CCS determination, HRIM addition to a HILIC-MS workflow provides confident fingerprinting of glycosylation profiles in biotherapeutics while enabling increased analytical throughput.
Pre-registration is not required. Just
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