Universal Metabolite Tagging
Universal Metabolite Tagging
批准号:
10240660
负责人:
Christopher K Arnatt
金额:
$44.04万
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
项目状态:
已结题
起止时间:
2019-09-15 至 2023-08-31
关键词:
AddressAffinityBindingBioinformaticsCarbonCardiacCationsChargeChemicalsClutteringsComputer ModelsCredentialingDataData AnalysesData SetDeuteriumDiabetes MellitusDigestive System DisordersDiseaseEvaluationExclusionGeographyHeart DiseasesHumanHuman bodyHydrophobicityInformaticsInjectionsInvestigationIslets of LangerhansIsotope LabelingIsotopesLaboratoriesMalignant NeoplasmsMass Spectrum AnalysisMetabolismMethodsModelingNoiseNutrientOutcomePathway interactionsPerformanceProcessProtocols documentationProtonsPunch BiopsyResearch PersonnelResolutionSaltsSamplingSchemeSeriesSignal TransductionSodium ChlorideSolventsStructureSystemTechnologyValidationVertebral columnadductbasebioinformatics toolcostdata complexitydata qualityfunctional groupimprovedinnovative technologieslarge datasetsliquid chromatography mass spectrometrymetabolomemetabolomicsnovelpiperidineresponsestemtargeted biomarkertechnology research and developmenttherapeutic targetvirtual
中文摘要
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英文摘要
Project Summary/Abstract
A major impediment to mass spectrometry based metabolomics unleashing its full potential is the
complexity of the data which is cluttered with solvent and salt adducts. This is called degeneracy
and gives multiple peaks from one analytes which diminish analyte signal and need to be
discarded using bioinformatic tools. In response to PAR-17-045 which calls for “focused
technology research and development,” a multi-PI team will develop a series of three distinct
chemical tagging platforms based on our recent universal proton affinity tags. These tags react
with virtually all metabolites and eliminate degeneracy, increase signal, allow for multi-charging,
and analysis of ultra-small samples. Aim 1 will develop a universal proton affinity tagging scheme
with multi-dimensional liquid chromatography mass spectrometry platform which allows for pre-
concentrating all metabolites and minimal degeneracy. Aim 2 will synthesize and develop two
sets of isotope labeled tags for ~$2/sample. The first set are isobaric tags for targeted analyses
using low resolution mass spectrometry. The second set are neucode based tags for high
resolution mass spectrometry capable of analyzing up to 60 samples simultaneously. Aim 3 uses
a novel tag which fragments across the carbon-carbon backbone to allow identification of new
metabolites using fragmentation modeling. In the final aim of the proposal we will leverage the
increase in sensitivity and multiplexing of the previous aims to analyze small samples. The
methods developed here will be evaluated for robustness and transferability by comparing
performance across multiple independent laboratories. The outcomes for this proposal are three
distinct technologies which solve multiple critical barriers in metabolomics.
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会议论文
Uncovering the roles of oxysterols in neuropathic pain
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批准号:10659247
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项目类别:
-
资助金额:$58.28万
-
财政年份:2022
-
负责人:Christopher K Arnatt
-
依托单位:
Uncovering the roles of oxysterols in neuropathic pain
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批准号:10504409
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项目类别:
-
资助金额:$52.03万
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财政年份:2022
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负责人:Christopher K Arnatt
-
依托单位:
海外基金