MoCeIS-DCL: Planning Workshops for Synthesis of Massively Parallel Assays and Molecular Physiology

MoCeIS-DCL：大规模并行分析和分子生理学综合规划研讨会

• 批准号: 2133405
• 负责人: Edward O'Brien
• 金额: $ 7.62万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2133405&HistoricalAwards=false
• 关键词: MoCeIS; DCL; Planning; Workshops; Synthesis

A diverse group of experimentalists, theorists, and computational experts will meet to design a communication framework that will maximize data sharing and integration and therefore current investments in research in the molecular biosciences. Workshop attendees will be tasked with a challenging question: how can one assemble the enormous amounts of data produced by distinct technologies, to answer apparently unrelated questions, so that one might see something beyond what the original experiments that produced the data sought to explore? Is there a way to synthesize the data acquired in distinct, individually focused experiments in such a way that one may obtain a global understanding of how multiple cellular processes are coordinately orchestrated? Could one then understand how distinct processes communicate, or regulate each other across multiple spatial, temporal, and energetic scales? A strategy to answer these questions can significantly increase the information one can extract from experimental data, and will ensure the participation of diverse investigators with their distinct perspectives.An unassembled mosaic of molecular physiology lies waiting to be synthesized from Massively Parallel (MP) Assays and high-throughput (HT) experiments, which have revolutionized molecular and cellular biology over the past decade. Three technologies underlie the hundreds of variants of these assays: Next-Generation Sequencing (NGS), mass spectrometry, and to a lesser extent, fluorescence. NGS-based MP assays, for example, can measure nearly all aspects of transcription, translation, and RNA degradation – from the location of every genome-bound transcription factor, DNA and RNA polymerase, every transcriptome-bound ribosome and ribosome bound factor at each stage of transcription and translation at nucleotide resolution, and the relative abundance of each mRNA. Mass spectrometry can report on interacting cellular components as well as their structural properties, while fluorescence techniques can monitor the real time location and kinetics of transcription and translation within cells. When coupled with pulse-chase strategies or high-throughput mutagenesis, these techniques can measure the rates of subcellular processes, detect essential molecular interactions, and characterize connections between genotype and phenotype. Thus, combining the nucleotide resolution of NGS-based techniques with the compositional and structural information from mass spec, and the spatio-temporal measurements from fluorescence, provides an opportunity for a multi-dimensional mosaic of molecular physiology to be created and synthesized with the quantitative and physical approaches characterizing NSF-MCB funded researchers. Furthermore, advances in artificial intelligence offers the opportunity to accelerate synthesis from these diverse datasets. A series of workshops to identify how the community can most efficiently use these data to promote synthesis will be held.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.

一个由实验学家、理论家和计算专家组成的多元化小组将开会设计一个通信框架，以最大限度地实现数据共享和整合，从而最大限度地提高目前对分子生物科学研究的投资。研讨会的参与者将面临一个具有挑战性的问题：如何收集不同技术产生的大量数据，回答显然不相关的问题，以便人们可以看到产生数据的原始实验试图探索的东西？有没有一种方法可以综合不同的、单独集中的实验中获得的数据，从而可以全面了解多个细胞过程是如何协调的？那么，人们是否能够理解不同的过程如何在多个空间、时间和能量尺度上相互沟通或调节？回答这些问题的策略可以显著增加从实验数据中提取的信息，并确保不同研究者以不同的视角参与进来。一个未组装的分子生理学马赛克正等待着从大规模并行（MP）分析和高通量（HT）实验中合成，这些实验在过去十年中彻底改变了分子和细胞生物学。这些检测的数百种变体背后有三种技术：下一代测序（NGS），质谱，以及在较小程度上的荧光。例如，基于NGS的MP测定法可以测量转录、翻译和RNA降解的几乎所有方面-从每个基因组结合的转录因子、DNA和RNA聚合酶的位置，每个转录组结合的核糖体和核糖体结合因子在核苷酸分辨率下的转录和翻译的每个阶段的位置，以及每个mRNA的相对丰度。质谱法可以报告相互作用的细胞组分及其结构特性，而荧光技术可以监测细胞内转录和翻译的真实的时间位置和动力学。当与脉冲追踪策略或高通量诱变相结合时，这些技术可以测量亚细胞过程的速率，检测必要的分子相互作用，并表征基因型和表型之间的联系。因此，将基于NGS的技术的核苷酸分辨率与来自质谱的组成和结构信息以及来自荧光的时空测量相结合，为创建和合成分子生理学的多维马赛克提供了机会，其中定量和物理方法表征了NSF-MCB资助的研究人员。此外，人工智能的进步为加速这些不同数据集的合成提供了机会。将举办一系列研讨会，以确定社区如何最有效地利用这些数据来促进综合。该奖项反映了NSF的法定使命，并被认为值得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来支持。