Glycosylation Profiling of Glycoproteins Secreted from Cultured Cells Using Glycan Node Analysis and GC-MS.

Szczegóły
Abstrakt

Tytuł:: Glycosylation Profiling of Glycoproteins Secreted from Cultured Cells Using Glycan Node Analysis and GC-MS.
Autorzy:: Aguilar Díaz de León JS; School of Molecular Sciences, The Biodesign Institute-Center for Personalized Diagnostics, Arizona State University, Tempe, AZ, USA.
Borges CR; School of Molecular Sciences, The Biodesign Institute-Center for Personalized Diagnostics, Arizona State University, Tempe, AZ, USA. .
Źródło:: Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2021; Vol. 2271, pp. 317-330.
Typ publikacji:: Journal Article
Język:: English
Imprint Name(s):: Publication: Totowa, NJ : Humana Press
Original Publication: Clifton, N.J. : Humana Press,
MeSH Terms:: Gas Chromatography-Mass Spectrometry*
Glycomics*
Protein Processing, Post-Translational*
Glycoproteins/*analysis
Hepatocytes/*metabolism
Immunoglobulin G/*analysis
Polysaccharides/*analysis
Culture Media, Conditioned/metabolism ; Glycosylation ; Hep G2 Cells ; Hepatocytes/drug effects ; Humans ; Interleukin-1beta/pharmacology ; Interleukin-6/pharmacology ; Methylation ; Neuraminidase/metabolism ; Research Design ; Secretory Pathway ; Workflow
References:: van Kooyk Y, Kalay H, Garcia-Vallejo JJ (2013) Analytical tools for the study of cellular glycosylation in the immune system. Front Immunol 4:451. https://doi.org/10.3389/fimmu.2013.00451. (PMID: 10.3389/fimmu.2013.00451243764493858669)
Hudak JE, Canham SM, Bertozzi CR (2014) Glycocalyx engineering reveals a Siglec-based mechanism for NK cell immunoevasion. Nat Chem Biol 10(1):69–75. (PMID: 10.1038/nchembio.1388)
Stanczak MA, Siddiqui SS, Trefny MP et al (2018) Self-associated molecular patterns mediate cancer immune evasion by engaging Siglecs on T cells. J Clin Investig 128(11):4912–4923. (PMID: 10.1172/JCI120612)
Qi J, Li N, Fan K et al (2014) β1,6 GlcNAc branches-modified PTPRT attenuates its activity and promotes cell migration by STAT3 pathway. PLoS One 9:e98052. https://doi.org/10.1371/journal.pone.0098052. (PMID: 10.1371/journal.pone.0098052248461754028250)
Rini JM, Esko JD (2017) Glycosyltransferases and glycan-processing enzymes. In: Varki A, Cummings RD, Esko JD et al (eds) Essentials of glycobiology, 3rd edn. Cold Spring Harbor, New York.
Varki A, Kannagi R, Toole B et al (2017) Glycosylation changes in cancer. In: Varki A, Cummings RD, Esko JD et al (eds) Essentials of glycobiology, 3rd edn. Cold Spring Harbor, New York.
Hossler P, Khattak SF, Li ZJ (2009) Optimal and consistent protein glycosylation in mammalian cell culture. Glycobiology 19:936–949. (PMID: 10.1093/glycob/cwp079)
Mackiewicz A, Schultz D, Mathison J, Ganapathi M, Kushner I (1989) Effect of cytokines on glycosylation of acute phase proteins in human hepatoma cell lines. Clin Exp Immunol 75(1):70–75. (PMID: 24677701541879)
Narisada M, Kawamoto S, Kuwamoto K et al (2008) Identification of an inducible factor secreted by pancreatic cancer cell lines that stimulates the production of fucosylated haptoglobin in hepatoma cells. Biochem Biophys Res Commun 377(3):792–796. (PMID: 10.1016/j.bbrc.2008.10.061)
Klasić M, Krištić J, Korać P et al (2016) DNA hypomethylation upregulates expression of the MGAT3 gene in HepG2 cells and leads to changes in N-glycosylation of secreted glycoproteins. Sci Rep 6:24363. https://doi.org/10.1038/srep24363. (PMID: 10.1038/srep24363270730204829869)
Drake RR, Jones EE, Powers TW, Nyalwidhe JO (2015) Altered glycosylation in prostate cancer. In: Drake RR, Ball LE (eds) Glycosylation and cancer. Advances in cancer research, vol 126. Elsevier, Amsterdam, pp 345–382.
Walsh G (2018) Biopharmaceutical benchmarks 2018. Nat Biotechnol 36(12):1136–1145. (PMID: 10.1038/nbt.4305)
Mulloy B, Dell A, Stanley P et al (2017) Structural analysis of glycans. In: Varki A, Cummings RD, Esko JD et al (eds) Essentials of glycobiology, 3rd edn. Cold Spring Harbor, New York.
Ciucanu I, Costello CE (2003) Elimination of oxidative degradation during the per-O-methylation of carbohydrates. J Am Chem Soc 125(52):16213–16219. (PMID: 10.1021/ja035660t)
Kang P, Mechref Y, Klouckova I, Novotny MV (2005) Solid-phase permethylation of glycans for mass spectrometric analysis. Rapid Commun Mass Spectrom 19(23):3421–3428. (PMID: 10.1002/rcm.2210)
Ciucanu I, Caprita R (2007) Per-O-methylation of neutral carbohydrates directly from aqueous samples for gas chromatography and mass spectrometry analysis. Anal Chim Acta 585(1):81–85. (PMID: 10.1016/j.aca.2006.12.015)
Kang P, Mechref Y, Novotny MV (2008) High-throughput solid-phase permethylation of glycans prior to mass spectrometry. Rapid Commun Mass Spectrom 22(5):721–734. (PMID: 10.1002/rcm.3395)
Borges CR, Rehder DS, Boffetta P (2013) Multiplexed surrogate analysis of glycotransferase activity in whole biospecimens. Anal Chem 85(5):2927–2936. (PMID: 10.1021/ac3035579)
Zaare S, Aguilar JS, Hu Y, Ferdosi S, Borges CR (2016) Glycan node analysis: A bottom-up approach to glycomics. J Vis Exp 2016(111):53961. https://doi.org/10.3791/53961. (PMID: 10.3791/53961)
Hu Y, Borges CR (2017) A spin column-free approach to sodium hydroxide-based glycan permethylation. Analyst 142(15):2748–2759. (PMID: 10.1039/C7AN00396J)
Ferdosi S, Ho TH, Castle EP et al (2018) Behavior of blood plasma glycan features in bladder cancer. PLoS One 13(7):e0201208. https://doi.org/10.1371/journal.pone.0201208. (PMID: 10.1371/journal.pone.0201208300408546057681)
Ferdosi S, Rehder DS, Maranian P et al (2018) Stage dependence, cell-origin independence, and prognostic capacity of serum glycan fucosylation, β1-4 branching, β1-6 branching, and α2-6 sialylation in cancer. J Proteome Res 17(1):543–558. (PMID: 10.1021/acs.jproteome.7b00672)
Hu Y, Ferdosi S, Kapuruge EP et al (2019) Diagnostic and prognostic performance of blood plasma glycan features in the women epidemiology lung cancer (WELCA) study. J Proteome Res 18(11):3985–3998. https://doi.org/10.1021/acs.jproteome.9b00457. (PMID: 10.1021/acs.jproteome.9b0045731566983)
Contributed Indexing:: Keywords: Aberrant Glycosylation; Antibody Glycosylation Profiling; Cell Culture Supernatant; GC-MS; Glycan Nodes; Glycan Permethylation; Glycans; Glycosylation Profiling; Secreted Glycoproteins
Substance Nomenclature:: 0 (Culture Media, Conditioned)
0 (Glycoproteins)
0 (IL1B protein, human)
0 (IL6 protein, human)
0 (Immunoglobulin G)
0 (Interleukin-1beta)
0 (Interleukin-6)
0 (Polysaccharides)
EC 3.2.1.18 (Neuraminidase)
Entry Date(s):: Date Created: 20210428 Date Completed: 20210623 Latest Revision: 20210623
Update Code:: 20240104
DOI:: 10.1007/978-1-0716-1241-5_22
PMID:: 33908017
: Czasopismo naukowe

Glycan "node" analysis is the process by which pooled glycans within complex biological samples are chemically deconstructed in a way that facilitates the analytical quantification of uniquely linked monosaccharide units (glycan "nodes"). It is based on glycan methylation analysis (a.k.a. linkage analysis) that has historically been applied to pre-isolated glycans. Thus, when using glycan node analysis, unique glycan features within whole biospecimens such as "core fucosylation," "α2-6 sialylation," "β1-6 branching," "β1-4 branching," and "bisecting GlcNAc," are captured as single analytical signals by GC-MS. Here we describe the use of this methodology in cell culture supernatant and in the analysis of IgG (alpha-1 antitrypsin) glycans. The effect of IL-6 and IL-1β cytokines on secreted hepatocyte protein glycan features is demonstrated; likewise, the impact of neuraminidase treatment of IgG is illustrated. For the majority of glycan nodes, the assay is consistent and reproducible on a day-to-day basis; because of this, relatively subtle shifts in the relative abundance of glycan features can be captured using this approach.

Informacja