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使用实时库搜索进行糖蛋白质组学的自主解离类型选择

Autonomous Dissociation-type Selection for Glycoproteomics Using a Real-Time Library Search.

作者信息

Sutherland Emmajay, Veth Tim S, Barshop William D, Russell Jacob H, Kothlow Kathryn, Canterbury Jesse D, Mullen Christopher, Bergen David, Huang Jingjing, Zabrouskov Vlad, Huguet Romain, McAlister Graeme C, Riley Nicholas M

机构信息

Department of Chemistry, University of Washington, Seattle, Washington 98195, United States.

Thermo Fisher Scientific, San Jose, California 95134, United States.

出版信息

J Proteome Res. 2024 Dec 6;23(12):5606-5614. doi: 10.1021/acs.jproteome.4c00723. Epub 2024 Nov 12.

Abstract

Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for glycopeptides, while electron-driven dissociation is crucial for site localization in glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both and glycopeptides within the same LC-MS/MS acquisition.

摘要

串联质谱(MS/MS)是完整糖肽鉴定的金标准,能够阐明肽序列并确定聚糖组成的位点特异性定位。对于糖肽而言,束型碰撞激活通常就足够了,而电子驱动解离对于糖肽的位点定位至关重要。现代糖蛋白质组学方法通常在单次液相色谱 - 串联质谱(LC-MS/MS)分析中采用多种解离技术,但这种方法在同时分析多种糖肽类别时常常会牺牲灵敏度。在此,我们通过实时库搜索(RTLS)探索智能数据采集在糖蛋白质组学中的效用,以匹配鎓离子模式,从而即时选择合适的解离方法。通过将解离方法与糖肽类别相匹配,这种自主解离类型选择(ADS)相对于传统束型碰撞激活方法产生了等量的糖肽鉴定结果,同时相对于传统基于电子转移解离的方法也产生了相当数量的位点定位糖肽鉴定结果。ADS方法通过在同一LC-MS/MS采集中实现对糖肽和位点特异性的表征,代表了糖蛋白质组学通量方面的一个进步。

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