Literature DB >> 27743370

Automated Integration of a UPLC Glycomic Profile.

Anna Agakova1, Frano Vučković2, Lucija Klarić2, Gordan Lauc2, Felix Agakov3.   

Abstract

Ultra-performance liquid chromatography (UPLC) is the established technology for accurate analysis of IgG Fc N-glycosylation due to its superior sensitivity, resolution, speed, and its capability to provide branch-specific information of glycan species. Correct and cost-efficient preprocessing of chromatographic data is the major prerequisite for subsequent analyses ranging from inference of structural isomers to biomarker discovery and prediction of humoral immune response from characterized changes in glycosylation. The complexity of glycomic chromatograms poses a number of challenges for developing automated data annotation and quantitation algorithms, which frequently necessitated manual or semi-manual approaches to preprocessing, most notably to peak detection and integration. Such procedures are meticulous and time-consuming, and may be a source of confounding due to their dependence on human labelers. Although liquid chromatography is a mature field and a number of methods have been developed for automatic peak detection outside the area of glycomics analysis, we found that hardly any of them are suitable for automatic integration of UPLC glycomic profiles without substantial modifications. In this chapter, we illustrate practical challenges of automatic peak detection of UPLC glycomics chromatograms. We outline a robust, semi-supervised method ACE (Automatic Chromatogram Extraction) for automated alignment and detection of glycan peaks in chromatograms, developed by Pharmatics Limited (UK) in collaboration with Genos Limited (Croatia). Application of the tool requires minimal human interference, which results in a significant reduction in the time and cost of IgG glycomics signal integration using Waters Acquity UPLC instrument (Milford, MA, USA) in several human cohorts with blind technical replicas.

Entities:  

Keywords:  Automatic alignment; Data analysis; Glycomics; Liquid chromatography; Peak detection

Mesh:

Substances:

Year:  2017        PMID: 27743370     DOI: 10.1007/978-1-4939-6493-2_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  5 in total

1.  Children at onset of type 1 diabetes show altered N-glycosylation of plasma proteins and IgG.

Authors:  Najda Rudman; Domagoj Kifer; Simranjeet Kaur; Vesna Simunović; Ana Cvetko; Flemming Pociot; Grant Morahan; Olga Gornik
Journal:  Diabetologia       Date:  2022-05-27       Impact factor: 10.460

2.  Plasma N-glycome shows continuous deterioration as the diagnosis of insulin resistance approaches.

Authors:  Ana Cvetko; Massimo Mangino; Cristina Menni; Olga Gornik; Marko Tijardović; Domagoj Kifer; Mario Falchi; Toma Keser; Markus Perola; Tim D Spector; Gordan Lauc
Journal:  BMJ Open Diabetes Res Care       Date:  2021-09

Review 3.  Aberrant glycosylation and cancer biomarker discovery: a promising and thorny journey.

Authors:  Mengmeng Wang; Jianhui Zhu; David M Lubman; Chunfang Gao
Journal:  Clin Chem Lab Med       Date:  2019-03-26       Impact factor: 8.490

4.  HappyTools: A software for high-throughput HPLC data processing and quantitation.

Authors:  Bas Cornelis Jansen; Lise Hafkenscheid; Albert Bondt; Richard Andrew Gardner; Jenifer Lynn Hendel; Manfred Wuhrer; Daniel Ian Richard Spencer
Journal:  PLoS One       Date:  2018-07-06       Impact factor: 3.240

5.  Immunoglobulin G glycome composition in transition from premenopause to postmenopause.

Authors:  Helena Deriš; Domagoj Kifer; Ana Cindrić; Tea Petrović; Ana Cvetko; Irena Trbojević-Akmačić; Ivana Kolčić; Ozren Polašek; Louise Newson; Tim Spector; Cristina Menni; Gordan Lauc
Journal:  iScience       Date:  2022-02-10
  5 in total

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