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Immunoglobulin G Glycoprofiles are Unaffected by Common Bottom-Up Sample Processing

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Figshare2020-09-18 更新2026-04-28 收录
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Immunoglobulin G (IgG) glycosylation is a key post-translational modification in regulating IgG function. It is therefore a prominent target for biomarker discovery and a critical quality attribute of antibody-based biopharmaceuticals. A common approach for IgG glycosylation analysis is the measurement of tryptic glycopeptides. Glycosylation stability during sample processing is a key prerequisite for an accurate and robust analysis yet has hitherto hardly been studied. Especially, acid hydrolysis of sialic acids may be a source for instability. Therefore, we investigated acid denaturation, centrifugal vacuum concentration, and glycopeptide storage regarding changes in the IgG glycosylation profile. Intravenous IgG was analyzed employing imaginable deviations from a reference method and stress conditions. All glycosylation features sialylation, galactosylation, bisection, and fucosylationremained unchanged for most conditions. Only with prolonged exposure to acidic conditions at 37 °C, sialylation decreased significantly and subtle changes occurred for galactosylation. Consequently, provided that long or intense heating in acidic solutions is avoided, sample preparation for bottom-up glycoproteomics does not introduce conceivable biases.

免疫球蛋白G(Immunoglobulin G, IgG)糖基化是调控IgG功能的关键翻译后修饰(post-translational modification),因此其既是生物标志物发现的重要靶点,也是抗体类生物制药的关键质量属性。当前用于IgG糖基化分析的常用方法为检测胰蛋白酶酶解糖肽(tryptic glycopeptides)。样品处理过程中的糖基化稳定性是实现准确且可靠分析的核心前提,但迄今为止相关研究仍较为匮乏。其中,唾液酸(sialic acids)的酸水解(acid hydrolysis)可能是导致稳定性波动的诱因之一。为此,我们针对IgG糖基化谱的变化,考察了酸变性(acid denaturation)、离心真空浓缩(centrifugal vacuum concentration)以及糖肽储存(glycopeptide storage)三个环节的影响。实验采用偏离参考方法的各类可能情况与应激条件(stress conditions),对静脉注射用IgG进行了分析。所有糖基化特征——包括唾液酸化(sialylation)、半乳糖基化(galactosylation)、平分型糖基化(bisection)与岩藻糖基化(fucosylation)——在绝大多数实验条件下均未发生显著改变。仅当样品在37℃酸性条件下长时间暴露时,唾液酸化水平才会出现显著下降,半乳糖基化也伴随出现细微变化。综上,只要避免酸性溶液中长时间或高强度加热,自下而上糖蛋白质组学(bottom-up glycoproteomics)的样品制备流程不会引入可预见的分析偏差。

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2020-09-18
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