A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
使用冷冻电子断层扫描以近原子分辨率原位结构测定的计算平台
基本信息
- 批准号:10466802
- 负责人:
- 金额:$ 31.82万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-01 至 2025-05-31
- 项目状态:未结题
- 来源:
- 关键词:AchievementAdoptionAlgorithm DesignAlgorithmsBenchmarkingBiologicalBiologyBiomedical ResearchCellsClassificationCommunitiesComplexComputer softwareComputing MethodologiesCryo-electron tomographyCryoelectron MicroscopyDataData AnalysesData CollectionData SetDevelopmentDisciplineDiseaseDoseElectron MicroscopeEnvironmentEnzymesExcisionFreezingGenerationsGeometryGoalsHybridsHydration statusImageImaging TechniquesImaging technologyIn SituIn VitroMapsMedicalMethodsMicroscopyModelingModernizationMolecularMolecular StructureMolecular WeightOutcomePerformancePlayPreparationProteinsResearchResolutionRoentgen RaysRoleRouteSamplingSeriesSpecimenStructureSystemTechniquesTechnologyTestingVisualizationX-Ray Crystallographyalgorithm developmentcombatcomputational platformcomputerized data processingcomputerized toolsdesignexperiencehigh resolution imagingimage processingimprovedinnovationinterestmacromoleculemolecular assembly/self assemblynanometer resolutionnovelopen sourceoverexpressionparticleprotein complexprotein structureprototypepublic health relevancereconstitutionreconstructiontechnology developmentthree dimensional structuretomographytool
项目摘要
PROJECT SUMMARY
Understanding how proteins interact within the cell to perform specific functions is a major goal of modern
biology, and vital for understanding the diverse roles these molecules play in biomedicine. Cryo-electron
tomography (cryo-ET) combined with sub-volume averaging (SVA) is currently the only imaging technology that
allows imaging macromolecules within their unperturbed native environment at nanometer resolutions. Most
successful studies, however, have been of large complexes or supramolecular assemblies, and at resolutions
that are too low to reveal molecular level interactions. The overall objective of this Technology Development
project is to design computational tools to improve the resolution of cryo-ET/SVA and extend its applicability to
a wider class of biomedically relevant targets. The specific aims are: (1) we will develop strategies to improve
the accuracy of the tilted contrast transfer function determination from low-dose tomographic projections, (2) we
will design algorithms to improve the accuracy of sub-volume alignment, reconstruction and classification aimed
at reducing the computational B-factors associated with data processing, and (3) we will optimize imaging and
data processing parameters to enable high-resolution studies of a wider class of targets including small
complexes. As proof of principle, we implemented a first-generation prototype of our platform and tested it on
monodisperse samples imaged by cryo-ET. The preliminary results demonstrate that our platform: (1) improves
the state-of-the-art in terms of achievable resolution, and (2) can be used to determine the structure of a 300kDa
enzyme at 3.9 Å resolution, representing a ground-breaking achievement for the field. Our research is innovative
because it seeks to overcome fundamental technical challenges in cryo-ET needed to realize the full potential of
this emerging imaging technology. The proposal is significant because it will be the first demonstration that low-
molecular weight targets can be imaged at near-atomic resolution using cryo-ET, indicating that this technique
is the most promising route for imaging important biomolecules in-situ. Ultimately, by closing the “resolution gap”
between strategies for studying monodisperse samples at high-resolution (X-ray, NMR and single-particle cryo-
EM) and techniques to study proteins in their native environments, our methods will allow the visualization of
protein complexes in their functional state at unprecedented levels of detail.
项目摘要
了解蛋白质如何在细胞内相互作用以执行特定功能是现代生物学的一个主要目标。
这些分子在生物医学中扮演着不同的角色。低温电子
与子体积平均(SVA)相结合的断层摄影(cryo-ET)是目前唯一的成像技术,
允许以纳米分辨率对未受干扰的天然环境中的大分子进行成像。最
然而,成功的研究是大的复合物或超分子组装,
太低而不能揭示分子水平的相互作用。本技术开发的总体目标
该项目旨在设计计算工具来提高cryo-ET/SVA的分辨率并扩展其适用性,
更广泛的生物医学相关目标。具体目标是:(1)我们将制定战略,
从低剂量断层投影确定倾斜对比度传递函数的准确性,(2)我们
将设计算法来提高子体积对齐、重建和分类的准确性,
减少与数据处理相关的计算B因子,以及(3)我们将优化成像,
数据处理参数,以便能够对更广泛类别的目标进行高分辨率研究,包括小型
配合物作为原理证明,我们实现了平台的第一代原型,并在
通过cryo-ET成像的单分散样品。初步结果表明,我们的平台:(1)提高
在可实现的分辨率方面的最新技术水平,和(2)可用于确定300 kDa的结构
酶在3.9毫米分辨率,代表了该领域的突破性成就。我们的研究是创新的
因为它试图克服低温ET所需的基本技术挑战,以实现
这种新兴的成像技术。该提案意义重大,因为这将是第一次证明低-
分子量的目标可以成像在近原子分辨率使用冷冻ET,表明这种技术
是原位成像重要生物分子的最有前途的途径。最终,通过缩小“分辨率差距”,
在高分辨率下研究单分散样品的策略(X射线,NMR和单颗粒低温)之间,
EM)和技术来研究蛋白质在其天然环境中,我们的方法将允许可视化
蛋白质复合物在其功能状态在前所未有的细节水平。
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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Alberto Bartesaghi其他文献
Alberto Bartesaghi的其他文献
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{{ truncateString('Alberto Bartesaghi', 18)}}的其他基金
A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
使用冷冻电子断层扫描以近原子分辨率原位结构测定的计算平台
- 批准号:
10624852 - 财政年份:2021
- 资助金额:
$ 31.82万 - 项目类别:
A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
使用冷冻电子断层扫描以近原子分辨率原位结构测定的计算平台
- 批准号:
10581369 - 财政年份:2021
- 资助金额:
$ 31.82万 - 项目类别:
A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
使用冷冻电子断层扫描以近原子分辨率原位结构测定的计算平台
- 批准号:
10183362 - 财政年份:2021
- 资助金额:
$ 31.82万 - 项目类别:
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