GRable 1.0 版:用于特定位点糖形分析的软件工具,改进了基于 MS1 的糖肽检测,并利用 MS2 信息进行平行聚类和置信度评估。

IF 6.1 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Molecular & Cellular Proteomics Pub Date : 2024-09-01 Epub Date: 2024-08-23 DOI:10.1016/j.mcpro.2024.100833
Chiaki Nagai-Okatani, Daisuke Tominaga, Azusa Tomioka, Hiroaki Sakaue, Norio Goda, Shigeru Ko, Atsushi Kuno, Hiroyuki Kaji
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引用次数: 0

摘要

高通量的完整糖肽分析对于阐明每种糖蛋白上附着的聚糖的生理和病理状态至关重要。由于糖蛋白结构的多样性和异质性,基于质谱的糖蛋白组学方法具有挑战性。因此,我们开发了一种基于 MS1 的位点特异性糖形分析方法,名为 "基于糖异质性的洗脱图谱糖肽信号关系识别(Glyco-RIDGE)",以进行更全面的分析。该方法根据糖肽的质量和色谱特性将糖肽信号检测为一个群集,然后通过匹配其质量和保留时间差异来搜索核心肽和糖组成的每种组合。在此,我们开发了一种名为 GRable 的基于浏览器的新型软件,用于半自动化 Glyco-RIDGE 分析,该软件显著改进了糖肽检测算法,包括 "并行聚类"。这一独特的功能提高了糖肽检测的全面性,并使分析能够集中于特定的糖结构,如pauci-甘露糖。另一项显著的改进是评估 GRable 结果的 "置信度",特别是使用 MS2 信息。这一功能有助于减少核心肽和聚糖组成的错误配对,并改进对结果的解释。该算法的其他改进点包括:"校正功能",用于准确提取单异位峰;簇和核心肽的一一对应,即使是多重糖苷化的糖肽;以及 "簇间分析 "功能,用于了解检测到但不匹配的簇的原因。使用纯化和粗制糖蛋白样本证明了这些改进的意义,表明 GRable 可以对完整的糖基化糖蛋白进行大规模和深入的特定位点糖形分析。因此,该软件将帮助我们分析聚糖的状态和变化,通过补充基于MS2的糖蛋白组学的全面性,获得蛋白质糖基化的生物学和临床见解。GRable可通过GlyCosmos门户网站(https://glycosmos.org/grable)使用网络浏览器免费在线运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information.

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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