Identification of glycan branching patterns using multistage mass spectrometry with spectra tree analysis.,Journal of Proteomics

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Identification of glycan branching patterns using multistage mass spectrometry with spectra tree analysis.
Journal of Proteomics ( IF 2.8 ) Pub Date : 2020-01-21 , DOI: 10.1016/j.jprot.2020.103649
Hui Wang ₁ , Jingwei Zhang ₂ , Junchuan Dong ₁ , Meijie Hou ₁ , Weiyi Pan ₁ , Dongbo Bu ₁ , Jinyu Zhou ₃ , Qi Zhang ₁ , Yaojun Wang ₄ , Keli Zhao ₃ , Yan Li ₃ , Chuncui Huang ₃ , Shiwei Sun ₁

Affiliation

Glycans are crucial to a wide range of biological processes, and their biological activities are closely related to the branching patterns of structures. Different from the simple linear chains of proteins, branching patterns of glycans are more complicated, making their identification extremely challenging. Tandem mass spectrometry (MS2) cannot provide sufficient structural information to deduce glycan branching patterns even with the assistance of various bioinformatic tools and algorithms.The promising technology to identify glycan branching patterns is multi-stage mass spectrometry (MSn). The production-relationship among MSn spectra of a glycan is essentially a tree, making deducing glycan structures from MSn spectra a great challenge. In the present study, we report an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to fully exploit the information contained in the MSn spectra tree for glycan identification. Using 14 glycan standards, including 2 pairs with isomeric sequence, and 16 complex N-glycans isolated from RNase B and IgG, we demonstrated the successful application of glyBranch to branching pattern analysis. The source code of glyBranch is available at https://github.com/bigict/glyBranch/. We have also developed a web-server, which is freely accessible at http://glycan.ict.ac.cn/glyBranch/. SIGNIFICANCE: Glycans are crucial in various biological processes and their functions are closely related to the details of their structures; thus, the identification of glycan branching patterns is of great significance to biological studies. Multistage mass spectrometry (MSn) can provide detailed structural information by generating multiple-level fragments through consecutive fragmentation; however, the interpretation of numerous MSn spectra is extremely challenging. In this study, we present an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to exploit the information contained in MSn spectra tree for glycan identification. This approach will greatly facilitate the automated identification of glycan structures and related biological studies.

中文翻译：

使用多级质谱分析和光谱树分析识别聚糖支化模式。

聚糖对广泛的生物过程至关重要，它们的生物活性与结构的分支模式密切相关。与简单的蛋白质线性链不同，聚糖的分支模式更为复杂，使其鉴定极具挑战性。即使借助各种生物信息学工具和算法，串联质谱（MS2）也无法提供足够的结构信息来推断聚糖的分支模式。鉴定聚糖分支模式的有前途的技术是多阶段质谱（MSn）。聚糖的MSn光谱之间的生产关系本质上是一棵树，使得从MSn光谱推导聚糖结构成为一个巨大的挑战。在目前的研究中，我们报告了一种称为glyBranch（基于光谱树的聚糖分支模式识别）的方法，可以充分利用MSn光谱树中包含的信息进行聚糖识别。使用14种聚糖标准品（包括2对具有同分异构序列的聚糖）和16种从RNase B和IgG中分离出的复杂N-聚糖，我们证明了glyBranch在分支模式分析中的成功应用。glyBranch的源代码位于https://github.com/bigict/glyBranch/。我们还开发了一个Web服务器，可以从http://glycan.ict.ac.cn/glyBranch/免费访问。意义：聚糖在各种生物过程中至关重要，其功能与它们的结构细节密切相关。因此，聚糖支链模式的鉴定对生物学研究具有重要意义。多级质谱（MSn）可以通过连续碎片生成多级碎片来提供详细的结构信息；然而，众多MSn光谱的解释极具挑战性。在这项研究中，我们提出了一种称为glyBranch（基于光谱树的聚糖分支模式识别）的方法，以利用MSn光谱树中包含的信息进行聚糖识别。这种方法将极大地促进聚糖结构的自动鉴定和相关的生物学研究。我们提出一种称为glyBranch（基于光谱树的聚糖分支模式识别）的方法，以利用MSn光谱树中包含的信息进行聚糖识别。这种方法将极大地促进聚糖结构的自动鉴定和相关的生物学研究。我们提出一种称为glyBranch（基于光谱树的聚糖分支模式识别）的方法，以利用MSn光谱树中包含的信息进行聚糖识别。这种方法将极大地促进聚糖结构的自动鉴定和相关的生物学研究。

更新日期：2020-01-22

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