High-Throughput De Novo Glycan Sequencing
高通量从头聚糖测序
基本信息
- 批准号:10000171
- 负责人:
- 金额:$ 44.73万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-01 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdoptedAlgorithm DesignAlgorithmsAnabolismAutoimmune DiseasesBehaviorBindingBioinformaticsBiologicalBiological MarkersBiomedical ResearchBiopolymersCarbonCardiovascular DiseasesCell AdhesionCommunitiesComplexComplex MixturesComputer softwareCouplingDataData SetDatabasesDevelopmentDiseaseDissociationEffectivenessElectron TransportEmbryonic DevelopmentEpitopesFourier transform ion cyclotron resonanceGenomeGlycoconjugatesGlycosidesHealthHigh Pressure Liquid ChromatographyImmune responseImpairmentIndividualIsomerismLinkLiquid ChromatographyLiquid substanceLung diseasesMachine LearningMalignant NeoplasmsMass Spectrum AnalysisMetabolicMethodsNatural graphiteNaturePathologic ProcessesPathway interactionsPatternPhasePhysiologicalPhysiological ProcessesPhysiologyPlayPolysaccharidesResearchResearch Project GrantsRoleSamplingSchemeSourceSpecificitySpeedStructureStructure-Activity RelationshipSurfaceVacuumVariantanalytical methodbasebioinformatics toolcatalystcell growthdesigngenetic linkage analysisglycosylationimprovedinstrumentmass spectrometernervous system disordernovelpathogenperformance testsprogramsprotein foldingreconstructiontandem mass spectrometrytherapeutic targettoolultraviolet
项目摘要
Glycosylation fulfills important physiological functions, including protein folding, embryogenesis, cell adhesion,
pathogen recognition, and immune response. The multifaceted roles glycosylation plays derive from the
presence of a range of glycan epitopes, where a small structural variation can have a profound impact on
functions. Further, a glycome consists of many closely related structures, with their relative amounts determined
by metabolic conditions in a cell- and growth-specific manner. Altered glycosylation is linked to many diseases,
including cardiovascular, pulmonary, neurological and autoimmune disorders, and cancer. Thus, there is a clear
need for analytical methods that can rapidly identify and quantify the many glycoforms in a glycome from different
health and disease states. Finally, no genome-predicted glycan database exists due to the unscripted nature of
glycan biosynthesis, and discovery of new glycan structures must be achieved by de novo methods.
Although tandem mass spectrometry-based biopolymer sequencing has been the major catalyst to the recent
rapid advance of 'omics, the prevailing collisionally activated dissociation method often fails to provide sufficient
glycan structural detail at the MS2 level, whereas the MSn approach lacks the speed, sensitivity, and quantitative
potential for high-throughput glycome analysis. We have recently developed an electronic excitation dissociation
(EED) method that can yield rich structural information in a single stage of MS/MS analysis. However, the impact
of EED on glycomics research is currently limited by its poor accessibility, insufficient coupling to on-line glycan
separation methods, and difficulty in interpretation of complex glycan EED tandem mass spectra.
Here, we propose to develop an integrated approach that combines EED with on-line liquid chromatography (LC)
separation and a novel bioinformatics tool to achieve high-throughput, de novo, and comprehensive glycome
characterization. We will explore the potential of EED for analysis of glycans in various derivatized forms, study
their fragmentation behaviors, and establish fragmentation rules for the development of bioinformatics software.
We will optimize conditions for efficient coupling of EED to reversed-phase, and porous graphitic carbon LC, and
develop an LC-EED-MS/MS approach for simultaneous characterization and quantitation of glycan mixtures. We
will implement EED on a Q-TOF instrument to improve its access to the glycoscience community. Finally, we will
develop and rigorously test the performance of a novel bioinformatics software that can rapidly and accurately
determine each glycan's structure from its tandem MS spectra. The proposed algorithm is fundamentally different
from most existing software, in that it no longer relies solely on glycosidic and cross-ring fragments for topology
and linkage analysis, but rather adopts a machine learning approach that considers the contexts of various types
of fragment peaks, and the spectral features associated with different linkage configurations and structural
motifs. The availability of such a high-throughput, de novo glycan sequencing tool will have an immense impact
on many biomedical research fields, as glycosylation plays critical roles in almost all biological pathways.
糖基化履行重要的生理功能,包括蛋白质折叠、胚胎发生、细胞粘附、
病原体识别和免疫反应。糖基化发挥的多方面作用源自
存在一系列聚糖表位,其中微小的结构变化可能会对
功能。此外,糖组由许多密切相关的结构组成,其相对数量已确定
以细胞和生长特异性的方式通过代谢条件。糖基化的改变与许多疾病有关,
包括心血管、肺、神经和自身免疫性疾病以及癌症。因此,有一个明确的
需要能够快速识别和量化来自不同来源的糖组中的多种糖型的分析方法
健康和疾病状态。最后,由于无脚本的性质,不存在基因组预测的聚糖数据库。
聚糖生物合成和新聚糖结构的发现必须通过从头方法来实现。
尽管基于串联质谱的生物聚合物测序已成为最近的主要催化剂
随着组学的快速发展,流行的碰撞激活解离方法往往无法提供足够的
MS2 水平的聚糖结构细节,而 MSn 方法缺乏速度、灵敏度和定量
高通量糖组分析的潜力。我们最近开发了一种电子激发解离
(EED) 方法可以在 MS/MS 分析的单个阶段中产生丰富的结构信息。然而,影响
EED 在糖组学研究中的应用目前受到其可及性差、与在线聚糖耦合不足的限制
分离方法,以及解释复杂聚糖 EED 串联质谱的困难。
在这里,我们建议开发一种将 EED 与在线液相色谱 (LC) 相结合的集成方法
分离和新型生物信息学工具,以实现高通量、从头和全面的糖组
表征。我们将探索 EED 用于分析各种衍生形式的聚糖的潜力,研究
其碎片行为,并为生物信息学软件的开发建立碎片规则。
我们将优化 EED 与反相和多孔石墨碳 LC 高效耦合的条件,以及
开发一种 LC-EED-MS/MS 方法,用于同时表征和定量聚糖混合物。我们
将在 Q-TOF 仪器上实施 EED,以改善其进入糖科学界的机会。最后,我们将
开发并严格测试新型生物信息学软件的性能,该软件可以快速准确地
从串联质谱图中确定每个聚糖的结构。所提出的算法根本不同
与大多数现有软件不同,它不再仅仅依赖糖苷和交叉环片段进行拓扑
和链接分析,而是采用考虑各种类型上下文的机器学习方法
碎片峰,以及与不同的连接构型和结构相关的光谱特征
主题。这种高通量、从头聚糖测序工具的可用性将产生巨大的影响
在许多生物医学研究领域,糖基化在几乎所有生物途径中都起着关键作用。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Pengyu Hong其他文献
Pengyu Hong的其他文献
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{{ truncateString('Pengyu Hong', 18)}}的其他基金
Identifying and addressing missingness and bias to enhance discovery from multimodal health data
识别和解决缺失和偏见,以增强多模式健康数据的发现
- 批准号:
10637391 - 财政年份:2023
- 资助金额:
$ 44.73万 - 项目类别:
Intelligent Interfaces for Interactive Analysis of High-Content Cellular Images
用于高内容细胞图像交互式分析的智能界面
- 批准号:
7470047 - 财政年份:2007
- 资助金额:
$ 44.73万 - 项目类别:
Intelligent Interfaces for Interactive Analysis of High-Content Cellular Images
用于高内容细胞图像交互式分析的智能界面
- 批准号:
7316890 - 财政年份:2007
- 资助金额:
$ 44.73万 - 项目类别:
Intelligent Interfaces for Interactive Analysis of High-Content Cellular Images
用于高内容细胞图像交互式分析的智能界面
- 批准号:
7617093 - 财政年份:2007
- 资助金额:
$ 44.73万 - 项目类别:
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