A semi-automated, high throughput approach for O-glycosylation profiling of in vitro established cancer cell lines by MALDI-FT-ICR MS.

Autor: Kotsias M; Ludger Ltd, Culham Science Centre, Abingdon, Oxfordshire, UK. maximilianos.kotsias@ludger.com., Madunić K; Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands., Nicolardi S; Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands., Kozak RP; Ludger Ltd, Culham Science Centre, Abingdon, Oxfordshire, UK., Gardner RA; Ludger Ltd, Culham Science Centre, Abingdon, Oxfordshire, UK., Jansen BC; Ludger Ltd, Culham Science Centre, Abingdon, Oxfordshire, UK., Spencer DIR; Ludger Ltd, Culham Science Centre, Abingdon, Oxfordshire, UK., Wuhrer M; Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands.
Jazyk: angličtina
Zdroj: Glycoconjugate journal [Glycoconj J] 2021 Dec; Vol. 38 (6), pp. 747-756. Date of Electronic Publication: 2021 Jul 20.
DOI: 10.1007/s10719-021-10003-1
Abstrakt: The study of protein O-glycosylation is important in biological research as O-glycans have been reported to regulate a multitude of molecular and cell biology processes occurring in cancer. It is known that alterations in O-glycosylation are involved in the development and progression of cancer. Their easy accessibility makes in vitro established cell lines suitable and useful models for studying biological mechanisms in disease. However, the O-glycosylation analysis of large numbers of samples, as required in systems biology and biomarker discovery studies, is often challenging. In the present study, O-glycans from three human colorectal cancer cell lines and two human pancreatic cancer cell lines were released by semi-automated, high throughput reductive β-elimination and analysed using ultrahigh resolution MALDI-FT-ICR MS. Automated data integration and processing was performed using MassyTools, where the analyte was automatically included for relative quantitation based on a range of selection criteria including signal-to-noise ratio, mass error and isotopic pattern quality scores. A total of 126 O-glycan compositions, ranging from a single monosaccharide to large oligosaccharides exhibiting complex glycan motifs, were detected. The use of ultrahigh resolution MALDI-FTICR MS enabled glycan identification and quantitation in the matrix region of the spectrum. This approach has the potential to be used for O-glycosylation analysis of large numbers of samples, such as patient sample cohorts.
(© 2021. The Author(s).)
Databáze: MEDLINE
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