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：
10624852
负责人：
Alberto Bartesaghi
金额：
$ 31.74万
依托单位：
DUKE UNIVERSITY
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：
https://reporter.nih.gov/project-details/10624852
关键词：
Acceleration Achievement Adoption Algorithm Design Algorithms Benchmarking Biological Biology Biomedical Research Cells Classification Communities Complex Computer software Computing Methodologies Cryo-electron tomography Cryoelectron Microscopy Data Data Analyses Data Collection Data Set Development Discipline Disease Dose Electron Microscope Environment Enzymes Excision Freezing Generations Geometry Goals Hybrids Hydration status Image Imaging Techniques Imaging technology In Situ In Vitro Maps Medical Methods Microscopy Modeling Modernization Molecular Molecular Structure Molecular Weight Outcome Performance Play Preparation Proteins Research Resolution Roentgen Rays Role Route Sampling Series Specimen Structure System Techniques Technology Testing Visualization X-Ray Crystallography algorithm development combat computational platform computerized data processing computerized tools design experience high resolution imaging image processing improved innovation interest macromolecule molecular assembly/self assembly nanometer resolution novel open source overexpression particle protein complex protein structure prototype public health relevance reconstitution reconstruction technology development three dimensional structure tomography tool

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目标的主要目标生物学，对于理解这些分子在生物医学中起的潜水作用至关重要。冷冻电子层析成像（Cryo-ET）与子体积平均（SVA）相结合是目前唯一的成像技术在纳米分辨率下，允许在其未受干扰的天然环境中成像大分子。最多然而，成功的研究是大型复合物或超分子组件，并且是分辨率太低，无法揭示分子水平的相互作用。这项技术开发的总体目标项目是设计计算工具来改善Cryo-ET/SVA的分辨率，并将其适用性扩展到一类更广泛的生物医学相关目标。具体目的是：（1）我们将制定改进的策略低剂量层析成像预测确定倾斜的对比度传输函数的准确性，（2）我们将设计算法以提高亚卷对齐，重建和分类的准确性在减少与数据处理相关的计算B因子时，（3）我们将优化成像和数据处理参数可以对更广泛的目标进行高分辨率研究，包括小复合物。作为原则的证明，我们实施了平台的第一代原型，并对其进行了测试 Cryo-Et成像的单分散样品。初步结果表明我们的平台：（1）改进就可实现的分辨率而言，最先进的方法，（2）可用于确定300kDa的结构分辨率为3.9Å的酶，代表该领域的开创性成就。我们的研究是创新的因为它试图克服Cryo-Et中需要的基本技术挑战，以实现全部潜力这项新兴成像技术。该提议很重要，因为这将是第一次证明分子量靶标可以使用冷冻-ET以接近原子的分辨率成像，表明该技术是对现场成像重要生物分子的最有希望的途径。最终，通过结束“解决方案差距” 在研究高分辨率的单分散样品的策略之间（X射线，NMR和单粒子冷冻 EM）和在其本地环境中研究蛋白质的技术，我们的方法将允许可视化蛋白质复合物处于其功能状态，处于前所未有的细节水平。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

nextPYP: a comprehensive and scalable platform for characterizing protein variability in situ using single-particle cryo-electron tomography.

DOI：
10.1038/s41592-023-02045-0
发表时间：
2023-12
期刊：
NATURE METHODS
影响因子：
48
作者：
Liu, Hsuan-Fu;Zhou, Ye;Huang, Qinwen;Piland, Jonathan;Jin, Weisheng;Mandel, Justin;Du, Xiaochen;Martin, Jeffrey;Bartesaghi, Alberto
通讯作者：
Bartesaghi, Alberto

Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography.

DOI：
10.1038/s41467-021-22251-8
发表时间：
2021-03-30
期刊：
Nature communications
影响因子：
16.6
作者：
Bouvette J;Liu HF;Du X;Zhou Y;Sikkema AP;da Fonseca Rezende E Mello J;Klemm BP;Huang R;Schaaper RM;Borgnia MJ;Bartesaghi A
通讯作者：
Bartesaghi A

High-resolution structure determination using high-throughput electron cryo-tomography.