Development of a Novel Technology for Preparative Fractionation and Characterization of Lipoprotein Particles
脂蛋白颗粒制备分级分离和表征新技术的开发
基本信息
- 批准号:10708003
- 负责人:
- 金额:$ 30.36万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-25 至 2026-06-30
- 项目状态:未结题
- 来源:
- 关键词:Activities of Daily LivingAcute DiseaseAddressAffinityAgeAntioxidantsApolipoprotein A-IApolipoproteinsBehaviorBindingBiologicalBiologyBiomedical ResearchCardiovascular DiseasesCharacteristicsChemicalsCholesterol EstersChronicChronic DiseaseClinicalCommunitiesComplementComplexCoupledDataDevelopmentDiagnosticDiameterDiseaseEthnic OriginExcisionExclusionExposure toFractionationGlucoseHealthHeterogeneityHigh Density LipoproteinsHigh Pressure Liquid ChromatographyIn VitroIndividualKnowledgeLipidsLipoprotein (a)LipoproteinsLongevityMass Spectrum AnalysisMeasurementMeasuresMediatorMetabolic Clearance RateMethodsMissionModificationMolecularMolecular Sieve ChromatographyNamesNational Institute of General Medical SciencesNatureNerve DegenerationNuclear Magnetic ResonanceOpticsOxidantsParticle SizePerformancePhysiologicalPlasmaPolysaccharidesProtein AnalysisProteinsPublishingRefractive IndicesResearchResearch PersonnelSamplingSepsisSeriesSignal TransductionStructureSystemTechnologyTherapeuticTransmission Electron MicroscopyValidationWomanacute infectionblood-brain barrier crossingdetectorexperimental studygel electrophoresisglycationglycosylationimmunoregulationimprovedinnovationinstrumentinstrumentationlight scatteringmenmortalitynew technologyoxidationparticlereceptorreconstitutiontheoriestherapeutically effective
项目摘要
Project Summary
High-density lipoproteins (HDL) are the single strongest predictors of longevity and protect against a wide array
of diseases, from chronic conditions like cardiovascular disease and neurodegeneration, to acute infection and
sepsis mortality, and everything in between. If we can get HDL right, we can live long, healthy lives. Yet despite
over 50 years of research, HDL have remained an enigma and therapeutic approaches for improving HDL
function have proven elusive. HDL are highly heterogeneous and difficult to isolate and characterize because of
their colloidal, multi-molecular nature yet very small size (< 20 nm in diameter). A critical barrier to progress is
the lack of technologies to simultaneously quantify the size and number of HDL particles, and isolate them such
that they remain intact and amenable for a variety of both compositional and functional analyses. The objectives
of this project are to gain new technological knowledge on the application of our instrument using size exclusion
chromatography coupled with multiple inline static and dynamic optical detectors, and to measure the
quantitative advantages of this technology over state-of-the-art approaches for the isolation and physicochemical
characterization of HDL particles. In particular, this project will solve the critical problem of quantifying the number
of particles using a non-destructive approach that simultaneously measures and fractionates the particles by
size, making it possible to evaluate the function and composition of different size-based HDL subclasses on a
per particle basis. Currently, researchers are limited by the simple problem of not having a good denominator:
the only option is to express the amount of an important constituent or functional capacity in the HDL we have
measured based on a rough substitute for “concentration” (e.g. total protein in the isolated fraction). Therefore,
if there is more of a certain protein (or higher functional capacity) in sample A vs. B, there is no way to distinguish
whether that is simply because sample A has more particles in it or whether there are more molecules of that
protein (or higher functional capacity) per particle. Different sizes of HDL carry different absolute and relative
amounts of individual proteins, lipids, and other components, from as few as 2 molecules of the main
apolipoprotein, apolipoprotein A-I, and 12 molecules of cholesteryl ester in the smallest HDL, to as many as 4-6
molecules of apolipoprotein A-I and hundreds of molecules of cholesteryl ester, with similar variability in the
concentrations of other critical components that confer dozens of functions, from antioxidant, to
immunomodulatory, to anti-proteolytic to name a few. And because particle size determines binding affinity to
receptors, clearance rates, and likely even whether HDL can cross the blood-brain-barrier, knowing the number
of particles of different sizes, and also the per particle composition of the cargo they carry is critical to the
development of sensitive, actionable diagnostics, and targeted, effective therapeutics. Thus, the technology
developed in this project will profoundly enable the biomedical research community to answer critical questions
about HDL functional biology across a broad array of clinical and therapeutic applications.
项目摘要
高密度脂蛋白(HDL)是长寿的单一最强预测因子,
从心血管疾病和神经退行性疾病等慢性疾病到急性感染,
脓毒症死亡率以及两者之间的一切。如果我们能正确获得HDL,我们就能活得健康长寿。然而尽管
经过50多年的研究,HDL仍然是一个谜,改善HDL的治疗方法
功能已被证明是难以捉摸的。HDL是高度异质性的,难以分离和表征,因为
它们的胶体、多分子性质,但尺寸非常小(直径< 20 nm)。进展的一个关键障碍是
缺乏同时量化HDL颗粒大小和数量的技术,并将其分离,
它们保持完整,并适合各种成分和功能分析。目标
本项目的目的是获得新的技术知识的应用,我们的仪器使用尺寸排阻
色谱法与多个在线静态和动态光学检测器耦合,并测量
与最先进的分离和物理化学方法相比,该技术的定量优势
HDL颗粒的表征。特别是,该项目将解决量化数量的关键问题
使用非破坏性方法同时测量和分离颗粒,
大小,使得有可能评估不同的基于大小的HDL子类的功能和组成,
每个粒子的基础上。目前,研究人员受到一个简单问题的限制,即没有一个好的分母:
唯一的选择是表达我们所拥有的HDL中重要成分或功能容量的量,
基于对“浓度”的粗略替代(例如,分离的级分中的总蛋白质)来测量。因此,我们认为,
如果样品A中某种蛋白质多于样品B(或功能能力更高),则无法区分
这是否仅仅是因为样品A中有更多的粒子,或者是否有更多的分子,
蛋白质(或更高的功能容量)/颗粒。不同大小的HDL携带不同的绝对值和相对值
单个蛋白质,脂质和其他成分的量,从少至2个分子的主要
载脂蛋白、载脂蛋白A-I和最小HDL中的12个胆固醇酯分子,多达4-6个
分子的载脂蛋白A-I和数百分子的胆固醇酯,具有相似的变异性,
其他关键成分的浓度,赋予几十种功能,从抗氧化剂,
免疫调节、抗蛋白水解等等。而且由于颗粒大小决定了与
受体,清除率,甚至可能是否HDL可以通过血脑屏障,知道的数字
不同尺寸的颗粒,以及它们所携带的货物的每颗粒组成对运输至关重要。
开发灵敏、可行的诊断方法和有针对性的有效治疗方法。因此,
在这个项目中开发的将深刻地使生物医学研究界能够回答关键问题
关于HDL的功能生物学在广泛的临床和治疗应用。
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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Angela M Zivkovic其他文献
Angela M Zivkovic的其他文献
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{{ truncateString('Angela M Zivkovic', 18)}}的其他基金
Development of a Novel Technology for Preparative Fractionation and Characterization of Lipoprotein Particles
脂蛋白颗粒制备分级分离和表征新技术的开发
- 批准号:
10503961 - 财政年份:2022
- 资助金额:
$ 30.36万 - 项目类别:
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