RAPID: Building a visual consensus model of the SARS-CoV-2 life cycle

RAPID：建立 SARS-CoV-2 生命周期的视觉共识模型

• 批准号: 2033695
• 负责人: Janet Iwasa
• 金额: $ 17.34万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2033695&HistoricalAwards=false
• 关键词: RAPID; Building; visual; consensus; model

The COVID-19 epidemic has motivated hundreds (if not thousands) of biological researchers around the globe to redirect their research efforts towards the understanding of SARS-CoV-2. This is leading to an explosion of data and it will be essential to find ways to rapidly digest and integrate new information into a context that facilitates consensus building in the research community. How do researchers and the broader community stay abreast of this flood of information? And how can we quickly move towards building a consensus model of the SARS-CoV-2 life cycle that builds on this explosive body of scientific data and expertise? This work proposes to take a novel and intuitive approach to facilitate scientific discourse and dissemination through the development of: (1) detailed molecular 3-D depictions that put a diverse dataset into the context of the SARS-CoV-2 life cycle, and; (2) provide for annotation tools to be used by researchers to explore and capture scientific discussions that will speed up consensus building to promote a mechanistic understanding of how this virus works. If successful, the work will reduce the time of consensus building from years to months. In addition, a graduate student and postdoc will receive training at the intersection of biological and computer sciences. Specifically, researchers will work with an international group of SARS-CoV-2 experts to develop detailed and accurate visualizations of all stages of the viral life cycle including cellular entry, RNA replication and transcription, and viral assembly and egress with known energy states, rates, and spatial accuracy. These 3-D visualizations, which will be made freely available online, will be used to stimulate discussions within the scientific community, and will be iteratively updated based on community feedback and new data. To facilitate consensus building, annotation tools will be developed to interactively describe the data used to generate the visualizations and will also mediate and capture scientific discourse surrounding the various molecular mechanisms involved in viral infection. This project will rapidly produce a rich and publicly accessible collection of knowledge about SARS-CoV-2 biology for the global community.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.

COVID-19疫情激励了地球仪数百（如果不是数千）生物研究人员将研究工作转向对SARS-CoV-2的理解。 这导致数据爆炸，必须找到快速消化新信息的方法，并将其整合到促进研究界建立共识的背景中。研究人员和更广泛的社区如何跟上这股信息洪流？我们如何才能迅速建立一个基于这些爆炸性的科学数据和专业知识的SARS-CoV-2生命周期的共识模型？这项工作建议采取一种新颖和直观的方法，以促进科学的话语和传播，通过发展：（1）详细的分子3-D解释，把不同的数据集的背景下，SARS冠状病毒的生命周期，和;（二）为研究人员提供注释工具，以探索和捕捉科学讨论，这将加快共识的建立，以促进一种机制了解这种病毒的运作方式。 如果成功，这项工作将把建立共识的时间从几年缩短到几个月。此外，研究生和博士后将接受生物科学和计算机科学交叉领域的培训。具体来说，研究人员将与一个国际SARS-CoV-2专家小组合作，开发病毒生命周期所有阶段的详细和准确的可视化，包括细胞进入，RNA复制和转录，以及已知能量状态，速率和空间精度的病毒组装和出口。这些3D可视化将在网上免费提供，将用于激发科学界的讨论，并将根据社区反馈和新数据进行迭代更新。 为了促进共识的建立，将开发注释工具来交互式地描述用于生成可视化的数据，并将介导和捕获围绕病毒感染所涉及的各种分子机制的科学论述。该项目将迅速为全球社区提供关于SARS-CoV-2生物学的丰富和可公开获取的知识集合。该奖项反映了NSF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。