Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
批准号:
10669037
负责人:
Ronghu Wu
金额:
$29.68万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-09-20 至 2025-07-31
关键词:
AcidsAffectBackBiological MarkersBiomedical ResearchBoronic AcidsCell SurvivalCellsClinicalComplexCovalent InteractionCultured CellsDataDendrimersDetectionDevelopmentDiseaseDrug TargetingEnzymesEventGlycopeptidesGlycoproteinsHealthHeterogeneityHumanInfectionKnowledgeLifeMalignant NeoplasmsMalignant neoplasm of ovaryMass Spectrum AnalysisMethodsMissionModificationMolecularPatientsPlayPolysaccharidesPost-Translational Protein ProcessingProtein AnalysisProtein GlycosylationProteinsProteomicsPublic HealthResearchRoleSamplingSiteStructureSurfaceTestingTissuesUnited States National Institutes of Healthbiological researchbiological systemsbiomarker discoverycellular developmentdensitydesigndisabilityearly detection biomarkersglycoproteomicsglycosylationhuman diseasehydroxyl groupinnovationinsightmonomernew therapeutic targetnoveloperationpotential biomarkerprotein functionsugar
中文摘要
点击翻译按钮获取中文摘要
英文摘要
SUMMARY
Glycosylation is one of the most common protein modifications and is essential for cell survival. Glycoproteins
contain a wealth of valuable information regarding the development and disease statuses of cells. Global
analysis of protein glycosylation aids in a better understanding of glycoprotein functions and the molecular
mechanisms of disease, and leads to the identification of glycoproteins as biomarkers. However, it is
extraordinarily challenging to comprehensively analyze glycoproteins because of the heterogeneity of glycans
and the low abundance of many glycoproteins. The objective of this project is to develop an innovative and
effective method to enrich glycopeptides with diverse glycan structures, especially those with low abundance,
and apply this method to globally and site-specifically analyze protein N- and O-glycosylation by mass
spectrometry (MS). Guided by strong preliminary data, this objective will be fulfilled by pursuing four specific
aims. 1) Effective enrichment of glycopeptides through the synergistic interactions using different types of
dendrimers. Based on the common feature that every glycan contains multiple hydroxyl groups, a novel method
benefiting from the synergistic interactions between a glycan and multiple boronic acid (BA) molecules
conjugated to one dendrimer will be developed to capture low-abundance glycopeptides. Different types of
dendrimers will be synthesized and tested, especially from monomers containing the 1→3 branching motif that
will increase the density of BA at the dendrimer surface and enhance the interactions with a glycan. 2)
Enhancement of the synergistic interactions by minimizing the steric effect and forming the ternary complex.
Different kinds of BAs will be studied, especially vinylboronic acids with a small size. This will decrease the steric
hindrance and strengthen the overall interaction between one glycan and BAs. Moreover, the formation of the
ternary complex will be studied to further enhance the interactions. 3) Global and site-specific analysis of O-
glycoproteins with glycan structure information. Through reversible covalent interactions, enriched glycopeptides
contain intact glycans, allowing for site-specific analysis of O-glycoproteins with glycan structure information.
This is especially important for O-glycosylation due to the lack of an enzyme to universally cleave O-glycans and
generate a common tag. 4) Comprehensive analysis of glycoproteins in tissues and sera from patients with
ovarian cancer. Combining the proposed method with multiplexed proteomics, glycoproteins in clinical samples
will be systematically and quantitatively analyzed. The results will provide insights into the molecular
mechanisms of the disease and lead to the discovery of biomarkers for early detection. Eventually, the best
dendrimer conjugated with the right BA will enable us to effectively capture low-abundance glycopeptides.
Because of the ease of operation and no sample restrictions, the method will have extensive applications in the
biological and biomedical research fields and will significantly advance glycoscience.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
Unraveling the surface glycoprotein interaction network by integrating chemical crosslinking with MS-based proteomics.
通过将化学交联与基于MS的蛋白质组学集成,从而揭示表面糖蛋白相互作用网络。
DOI:
10.1039/d0sc06327d
发表时间:
2021-01-04
期刊:
Chemical science
影响因子:
8.4
作者:
[Sun F, Suttapitugsakul S, Wu R]
通讯作者:
Wu R
DOI:
10.1021/acs.analchem.1c01935
发表时间:
2021-07-27
期刊:
Analytical chemistry
影响因子:
7.4
作者:
[Sun F, Suttapitugsakul S, Wu R]
通讯作者:
Wu R
DOI:
10.1002/anie.202102692
发表时间:
2021-05-10
期刊:
Angewandte Chemie (International ed. in English)
影响因子:
--
作者:
[Suttapitugsakul S, Tong M, Wu R]
通讯作者:
Wu R
Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
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批准号:10260575
-
项目类别:
-
资助金额:$29.79万
-
财政年份:2020
-
负责人:Ronghu Wu
-
依托单位:
Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
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批准号:10440467
-
项目类别:
-
资助金额:$29.27万
-
财政年份:2020
-
负责人:Ronghu Wu
-
依托单位:
Supplemental Funds for a Thermo Scientific Q Exactive HF Mass Spectrometer
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批准号:10384259
-
项目类别:
-
资助金额:$20.0万
-
财政年份:2020
-
负责人:Ronghu Wu
-
依托单位:
Effective MS-Based Methods for Unraveling Cell Surface Protein Interactions
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批准号:10671551
-
项目类别:
-
资助金额:$35.47万
-
财政年份:2017
-
负责人:Ronghu Wu
-
依托单位:
Effective MS-Based Methods for Unraveling Cell Surface Protein Interactions
-
批准号:10522689
-
项目类别:
-
资助金额:$34.98万
-
财政年份:2017
-
负责人:Ronghu Wu
-
依托单位:
Effective Methods to Globally Analyze Cell Surface Proteins and Glycoproteins
-
批准号:9239644
-
项目类别:
-
资助金额:$31.59万
-
财政年份:2017
-
负责人:Ronghu Wu
-
依托单位:
Effective Methods to Globally Analyze Cell Surface Proteins and Glycoproteins
-
批准号:9417031
-
项目类别:
-
资助金额:$34.85万
-
财政年份:2017
-
负责人:Ronghu Wu
-
依托单位:
海外基金