Ultra-Sensitive Multiplexed Quantification of Proteins Secreted from Single-Cells - Resubmission 01
对单细胞分泌的蛋白质进行超灵敏多重定量 - 重新提交 01
基本信息
- 批准号:9900024
- 负责人:
- 金额:$ 39.53万
- 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:2019-04-01 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:ART proteinAddressAntibodiesAreaBindingBiologicalBiological AssayCellsCellular AssayComplementConfusionDNADataDetectionDevelopmentDevicesEnsureEventGene Expression RegulationGrowth FactorHormonalImmuneImmunityIndividualInsulinInvestigationIslet CellLaboratoriesLifeMalignant NeoplasmsMeasurementMeasuresMedicalMetabolismMethodsMicrofluidic MicrochipsMicrofluidicsMolecularOrganismPeptidesPopulationProtein SecretionProteinsProteomicsReportingSignal PathwaySignal TransductionSignaling ProteinSorting - Cell MovementSpottingsSurfaceSystemTechniquesTechnologyTestingTimeWorkamplification detectionbasebiological information processingbiological systemscell typechemokinecytokinedigitalexperimental studygraphical user interfacehormonal signalsmicrofluidic technologyminiaturizenew technologyoperationpancreatic cancer cellspancreatic juiceprototypesingle cell proteinsuser friendly softwareuser-friendlywound healing
项目摘要
Ultra-Sensitive Multiplexed Quantification of Proteins Secreted from Single-Cells
This proposal aims to develop a powerful new technology for ultra-sensitive quantification of multiple proteins
secreted from single-cells. Secreted protein signals coordinate cellular and organism-level functions across
all biological systems, and their accurate quantification is crucial for understanding biological information
processing in general. Unfortunately, signaling studies have been hindered by poor sensitivity and limited
multiplexing ability of current proteomic methods, and the confusion of results due to pooling of multiple cell
readouts when conducting population-averaged assays. To address the need to quantify single-cell secreted
proteins across different signaling systems, we will develop a new microfluidic technology for ultra-sensitive,
multiplexed protein quantification at the single-cell level. We will use our wide-ranging expertise in single-cell
assay and microfluidic development and our extensive preliminary data to develop a user-friendly system
that will measure multiplexed protein signals from a wide range of cell types, in a time-dependent manner.
We will validate our method by quantifying signaling time courses of diverse systems including immune cells,
cancer secretion, and hormone signaling. This method will, for the first time, provide the means to gather
sensitive, multiplexed single-cell secreted protein measurements, and will be indispensable for
understanding signaling in immunity, metabolism, development and cancer.
单细胞分泌蛋白质的超灵敏多重定量
该提案旨在开发一种强大的新技术,用于对多种蛋白质进行超灵敏定量
由单细胞分泌分泌的蛋白质信号协调细胞和生物体水平的功能,
所有的生物系统,它们的精确量化对于理解生物信息至关重要。
一般的加工。不幸的是,信号传导研究一直受到灵敏度差和有限的阻碍,
当前蛋白质组学方法的多重化能力,以及由于多个细胞的合并而导致的结果混淆
进行群体平均分析时的读数。为了解决定量单细胞分泌的
蛋白质在不同的信号系统,我们将开发一种新的微流体技术,
单细胞水平的多重蛋白质定量。我们将利用我们在单细胞领域的广泛专业知识,
分析和微流体开发以及我们广泛的初步数据,以开发一个用户友好的系统
它将以时间依赖的方式测量来自各种细胞类型的多重蛋白质信号。
我们将通过量化包括免疫细胞在内的各种系统的信号传导时间过程来验证我们的方法,
癌症分泌和激素信号。这种方法将首次提供收集
灵敏的,多路复用的单细胞分泌蛋白测量,将是必不可少的,
了解免疫、代谢、发育和癌症中的信号传导。
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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{{ truncateString('Savas Tay', 18)}}的其他基金
Understanding robust cellular information processing in complex environments and development of enabling single-cell analysis technologies
了解复杂环境中强大的细胞信息处理以及单细胞分析技术的开发
- 批准号:
10552335 - 财政年份:2023
- 资助金额:
$ 39.53万 - 项目类别:
Ultra-Sensitive Multiplexed Quantification of Proteins Secreted from Single-Cells - Resubmission 01
对单细胞分泌的蛋白质进行超灵敏多重定量 - 重新提交 01
- 批准号:
10326373 - 财政年份:2019
- 资助金额:
$ 39.53万 - 项目类别:
Understanding Mechanisms of Robust Information Processing by NF-kappaB
了解 NF-kappaB 鲁棒信息处理的机制
- 批准号:
10371211 - 财政年份:2018
- 资助金额:
$ 39.53万 - 项目类别:
Understanding Mechanisms of Robust Information Processing by NF-kappaB
了解 NF-kappaB 鲁棒信息处理的机制
- 批准号:
9884554 - 财政年份:2018
- 资助金额:
$ 39.53万 - 项目类别:
Pilot Project: Application of microfluidics to in situ adaptive immunity
试点项目:微流控在原位适应性免疫中的应用
- 批准号:
9920104 - 财政年份:
- 资助金额:
$ 39.53万 - 项目类别:
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