MFB: Evaluating and Advancing Cryo-EM for RNA Conformational Ensembles

MFB：评估和推进 RNA 构象整体的冷冻电镜

• 批准号: 2330652
• 负责人: Rhiju Das
• 金额: $ 150万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-03-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330652&HistoricalAwards=false
• 关键词: MFB; Evaluating; Advancing; Cryo; EM

In this Molecular Foundations for Biotechnology project, Stanford faculty Rhiju Das and Wah Chiu will coordinate a team of expert collaborators to acquire foundational data sets and organize world-wide blind prediction challenges needed to resolve RNA motions. RNA molecules underlie the origin of life on Earth and fundamental processes across all modern life forms, ranging from viruses to humans to the microorganisms that dominate the planet’s fixation of carbon. Researchers currently imagine that most RNA molecules wiggle and shift shapes to carry out their functions, but experimentally visualizing the many conformations of any RNA has been difficult. The broader impacts of the proposed research include establishing standardized data sets and methods disseminated through challenges, publications, public data, and code to the broad community of scientists who are now focusing on RNA, including experts, biotechnology companies, academic trainees from underrepresented backgrounds, and citizen scientists who engage in RNA research through a long-standing video game called Eterna. If successful, this work will drive the development of methods that could be applied to visualize and dissect many RNA-based machines of biological or biotechnological interest. The proposed research has two aims: (1) to design, model, and experimentally probe RNA systems with discrete conformational states whose populations can be intentionally tuned, and (2) to characterize and challenge the broader artificial intelligence and computational communities to predict the continuous conformational ensembles of ribozymes, riboswitches, and synthetic RNAs. In both aims, the research will evaluate accuracy through double-blind studies in which predictions from one set of personnel – including independent labs, Eterna citizen scientists, and predictors in the biennial Critical Assessment of Structure Prediction – will be tested through experimental data collected by an independent set of personnel. The research will advance innovative interdisciplinary approaches, bringing together high-throughput RNA biochemistry, crowdsourcing, computer modeling, and cutting-edge cryogenic electron microscopy (cryo-EM) in the labs of the principal investigators, as well as the state of the art in deep learning research, molecular dynamics simulations, and sociology through collaborators and community-wide open science challenges. The research seeks to attain generality beyond any specific system through analysis of molecules drawn from viruses, bacteria, protozoans, metazoans, and from the imaginations of RNA nanotechnologists and citizen scientists. Finally, the research has the potential to benefit society through broader impacts in biotechnology and through educational opportunities involving direct mentorship of trainees from underrepresented racial and ethnic backgrounds and active learning through the Eterna citizen science platform and an Eterna Academy massive open online course.This project is supported by the Division of Chemistry in the Directorate for Mathematical and Physical Sciences, and by the Chemistry of Life Processes program in the Division of Chemistry.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在这个生物技术分子基础项目中，斯坦福大学教授Rhiju Das和Wah Chiu将协调一个专家合作团队来获取基础数据集，并组织解决RNA运动所需的全球盲预测挑战。RNA分子是地球上生命起源的基础，也是所有现代生命形式的基本过程的基础，从病毒到人类，再到主导地球碳固定的微生物。研究人员目前认为，大多数RNA分子通过摆动和改变形状来实现它们的功能，但通过实验可视化任何RNA的许多构象一直很困难。拟议研究的更广泛影响包括建立标准化的数据集和方法，通过挑战、出版物、公共数据和代码传播给现在专注于RNA的广大科学家社区，包括专家、生物技术公司、来自代表性不足背景的学术学员，以及通过长期存在的电子游戏《永恒》（Eterna）从事RNA研究的公民科学家。如果成功，这项工作将推动方法的发展，可以应用于可视化和解剖许多基于rna的生物或生物技术兴趣机器。提出的研究有两个目的：(1)设计，建模和实验探测具有离散构象状态的RNA系统，其种群可以有意调整；(2)表征和挑战更广泛的人工智能和计算社区，以预测核酶，核开关和合成RNA的连续构象集合。在这两个目标中，该研究将通过双盲研究来评估准确性，其中一组人员（包括独立实验室、Eterna公民科学家和两年一次的结构预测关键评估的预测者）的预测将通过一组独立人员收集的实验数据进行测试。该研究将推进创新的跨学科方法，在主要研究人员的实验室中汇集高通量RNA生物化学，众包，计算机建模和尖端低温电子显微镜（cryo-EM），以及通过合作者和社区范围内的开放科学挑战在深度学习研究，分子动力学模拟和社会学方面的最新技术。这项研究试图通过分析来自病毒、细菌、原生动物、后生动物以及RNA纳米技术专家和公民科学家的想象的分子，获得超越任何特定系统的普遍性。最后，这项研究有潜力通过对生物技术的更广泛影响，通过教育机会，包括对来自未被充分代表的种族和民族背景的受训者的直接指导，以及通过Eterna公民科学平台和Eterna学院大规模开放在线课程的积极学习，使社会受益。该项目由数学与物理科学理事会化学学部和化学学部生命过程化学项目支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。