Development of a Versatile Multiplexing Nanoscopy Platform for Cell Biology
细胞生物学多功能多重纳米显微镜平台的开发
基本信息
- 批准号:10753760
- 负责人:
- 金额:$ 62.14万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-25 至 2027-06-30
- 项目状态:未结题
- 来源:
- 关键词:3-DimensionalAccelerationAlgorithmsAlzheimer&aposs DiseaseAnatomyArchitectureAreaBiologicalBiologyBlinkingCell membraneCell physiologyCellsCellular biologyCiliaColorComplexCuesDNADataData SetDevelopmentDiabetes MellitusDiseaseElectron MicroscopyEpidermal Growth Factor ReceptorFaceFeedbackFunctional disorderFutureGoalsGolgi ApparatusImageImage AnalysisIndividualLabelLightLinkMalignant NeoplasmsMapsMedialMembraneMicrofluidicsMolecularMorphologyNanoscopyNeurodegenerative DisordersOrangesOrganellesPIK3CG genePathogenesisPhysicsPhysiologicalProteinsProto-Oncogene Proteins c-aktPublic HealthReagentReporterResolutionSamplingSignal TransductionSortingSpecificitySpeedSurfaceSystemTechniquesTechnologyValidationVisualizationautomated analysisbiological developmentciliopathycostdevelopmental diseaseextracellularflexibilityimaging approachimaging platformimprovedinnovationinsightinstrumentationinterestlight microscopymetermicrobialmultiplexed imagingnanonanoscalenanoscopenervous system disordernew technologynovelopen sourcesegregationsingle moleculesuperresolution imagingsuperresolution microscopytechnology validationultra high resolutionuser-friendly
项目摘要
Project Summary
Understanding cellular function is intimately linked with the ability to visualize organelle ultrastructure with
molecular specificity and to observe how it is altered in diseases such as cancer, neurological disease,
ciliopathies and microbial pathogenesis. Super-resolution microscopy (SRM) has potential here as it bridges
the gap between light and electron microscopy and provides molecular specificity. However, SRM mostly offers
only a few color channels. This prohibits a comprehensive architectural map of organelles, as many are
pleomorphic and exist in multiple states depending on intra- and extracellular cues, making the combination of
datasets, each showing different subsets of labels, difficult. The SRM technique of DNA-PAINT allows, in
principle, powerful multiplexing to image 10 or more labels in one sample, but hurdles in speed, cost and ease
of use have limited its application. What is needed is a highly versatile multiplexing strategy to enable SRM of
organelles with an order-of-magnitude improvement in four key areas: acquisition speed, switching between
multiplex probe sets, spatial resolution, and cost. This requires new probes, instrumentation, enhanced
analysis, and biological validation. We will approach these tasks through three Specific Aims: 1) the
development of new versatile, DNA-PAINT probes that are both fluorogenic and provide a fast, adaptable,
low-cost framework for multiplexing, 2) a new platform for automated acquisition of multiplex DNA-PAINT data
and analytics to ‘connect the dots’ of single-molecule localization points in three dimensions and thereby create
membrane representations of organelles, and 3) the development of multiplexed DNA-PAINT ‘organelle
modules’ to validate this technology under realistic biological conditions and lower the entrance hurdle for
future biological users. Achieving these aims and their concrete deliverables will have a wide impact on the use
and accessibility of SRM to accelerate biological discovery.
项目摘要
了解细胞功能与观察细胞器超微结构的能力密切相关
分子特异性,并观察它在癌症、神经疾病、
纤毛疾病和微生物发病机制。超分辨率显微镜(SRM)在这方面具有潜力,因为它架起了
光学显微镜和电子显微镜之间的间隙,并提供分子特异性。然而,SRM主要提供
只有几个颜色通道。这禁止了细胞器的全面体系结构图,因为许多细胞器都是这样
多形性,并根据细胞内和细胞外线索以多种状态存在,使得
每个数据集都显示了不同的标签子集,这是很困难的。DNA-Paint的SRM技术允许
原理上,强大的多路复用器可在一个样本中对10个或更多标签进行图像处理,但在速度、成本和易用性方面存在障碍
使用的限制了它的应用。我们需要的是一种高度通用的多路复用策略,以实现
细胞器在四个关键领域有了数量级的改进:获取速度,在
多路复用探头组、空间分辨率和成本。这需要新的探头、仪器、增强的
分析和生物验证。我们将通过三个具体目标来处理这些任务:1)
开发新的多功能DNA涂料探针,既能产生荧光,又能提供一种快速、适应性强、
低成本的多路复用框架;2)多路DNA-PAINT数据自动获取的新平台
以及分析,以在三维中将单分子定位点的点连接起来,从而创建
细胞器的膜表示;3)复合型DNA-Paint‘细胞器的发展
模块在现实的生物条件下验证这项技术,并降低进入门槛
未来的生物使用者。实现这些目标及其具体交付成果将对使用产生广泛的影响
以及SRM的可获得性,以加速生物发现。
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)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Joerg Bewersdorf其他文献
Joerg Bewersdorf的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Joerg Bewersdorf', 18)}}的其他基金
Development of pan-Expansion Microscopy to reveal mechanisms underlying epidermal differentiation
开发泛膨胀显微镜以揭示表皮分化的机制
- 批准号:
10662553 - 财政年份:2022
- 资助金额:
$ 62.14万 - 项目类别:
Development of pan-Expansion Microscopy to reveal mechanisms underlying epidermal differentiation
开发泛膨胀显微镜以揭示表皮分化的机制
- 批准号:
10539999 - 财政年份:2022
- 资助金额:
$ 62.14万 - 项目类别:
An Integrated Imaging System for High-throughput Nanoscopy of the 4D Nucleome
用于 4D 核组高通量纳米显微成像的集成成像系统
- 批准号:
9308968 - 财政年份:2015
- 资助金额:
$ 62.14万 - 项目类别:
相似海外基金
Shared and Distributed Memory Parallel Pre-Conditioning and Acceleration Algorithms for "Spline- Enhanced" Spatial Discretisations
用于“样条增强”空间离散化的共享和分布式内存并行预处理和加速算法
- 批准号:
2907459 - 财政年份:2023
- 资助金额:
$ 62.14万 - 项目类别:
Studentship
Efficient algorithms and succinct data structures for acceleration of telescoping and related problems
用于加速伸缩及相关问题的高效算法和简洁数据结构
- 批准号:
RGPIN-2021-03147 - 财政年份:2022
- 资助金额:
$ 62.14万 - 项目类别:
Discovery Grants Program - Individual
Acceleration framework for training deep learning by cooperative with algorithms and computer architectures
通过与算法和计算机架构合作训练深度学习的加速框架
- 批准号:
21K17768 - 财政年份:2021
- 资助金额:
$ 62.14万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Efficient algorithms and succinct data structures for acceleration of telescoping and related problems
用于加速伸缩及相关问题的高效算法和简洁数据结构
- 批准号:
RGPIN-2021-03147 - 财政年份:2021
- 资助金额:
$ 62.14万 - 项目类别:
Discovery Grants Program - Individual
Material and Device Building Blocks for Hardware Acceleration of Machine Learning and Artificial Intelligence Algorithms
用于机器学习和人工智能算法硬件加速的材料和设备构建模块
- 批准号:
2004791 - 财政年份:2020
- 资助金额:
$ 62.14万 - 项目类别:
Continuing Grant
CIF: Small: Collaborative Research: Acceleration Algorithms for Large-scale Nonconvex Optimization
CIF:小型:协作研究:大规模非凸优化的加速算法
- 批准号:
1909291 - 财政年份:2019
- 资助金额:
$ 62.14万 - 项目类别:
Standard Grant
Acceleration of trigger algorithms with FPGAs at the LHC implemented using higher-level programming languages
使用高级编程语言在 LHC 上使用 FPGA 加速触发算法
- 批准号:
ST/S005560/1 - 财政年份:2019
- 资助金额:
$ 62.14万 - 项目类别:
Training Grant
CIF: Small: Collaborative Research: Acceleration Algorithms for Large-scale Nonconvex Optimization
CIF:小型:协作研究:大规模非凸优化的加速算法
- 批准号:
1909298 - 财政年份:2019
- 资助金额:
$ 62.14万 - 项目类别:
Standard Grant
Acceleration of trigger algorithms with FPGAs at the LHC implemented using higher-level programming languages
使用高级编程语言在 LHC 上使用 FPGA 加速触发算法
- 批准号:
2348748 - 财政年份:2019
- 资助金额:
$ 62.14万 - 项目类别:
Studentship
OAC Core: Small: Enabling High-fidelity Turbulent Reacting-Flow Simulations through Advanced Algorithms, Code Acceleration, and High-order Methods for Extreme-scale Computing
OAC 核心:小型:通过高级算法、代码加速和超大规模计算的高阶方法实现高保真湍流反应流模拟
- 批准号:
1909379 - 财政年份:2019
- 资助金额:
$ 62.14万 - 项目类别:
Standard Grant