NSF-ANR: Cellular Crowding and Condensation Under Shear Flow

NSF-ANR：剪切流下的细胞拥挤和凝结

• 批准号: 2210228
• 负责人: Michael Feig
• 金额: $ 106.89万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2210228&HistoricalAwards=false
• 关键词: NSF; ANR; Cellular; Crowding; Condensation

Inside biological cells there is a highly concentrated mix of biomolecules, proteins and nucleic acids, that interact frequently. Most of these interactions are non-specific, but they may nevertheless lead to clustering, aggregation, and the formation of phase separated regions, all of which can have a significant impact on biological function. In this project, hydrodynamic flow present inside living cells is studied as a new dimension that is expected to modulate transient molecular interactions and enhance or suppress aggregation and phase separation as a consequence. The outcome of these efforts is a more complete, fully dynamic view of how biomolecules interact in dense biological environments. The project involves a close integration between biophysical experiments and computer simulations. There are synergistic benefits from international collaboration between US and French groups to develop complementary computational expertise for large-scale simulations of interacting biomolecules in the presence of external flow. The impact of the research activities is enhanced by extensive involvement of undergraduate and graduate students in highly interdisciplinary research with a strong focus on the continued recruitment and support of females and underrepresented minorities in biophysical research. The development of a new physics curriculum targeted at life science majors is another goal for making physics education more relevant for biology topics. In another direction, a public outreach component is developed where physical demonstrations are combined with computer simulations to illustrate the abstract concept of diffusion via particle interactions in the context of biology. In dense cellular environments biomolecules interact frequently via transient non-specific interactions. Such interactions may lead to clustering, condensation, and aggregation. Here the effect of shear flow on such processes is examined as a new dimension towards understanding the behavior of biomolecules in realistic biological environments. Shear flow is present in biological cells and is expected to modulate transient interactions and condensation and potentially facilitate aggregation. Different model systems will be investigated via experiments and computer simulations. The model systems include concentrated solutions of globular proteins to study non-condensing transient clustering, peptide-RNA mixtures to study condensation, and highly dynamic intrinsically disordered peptides to examine intra- and intermolecular diffusion in crowded and condensing environments. Experiments involve nano-scale spectroscopy and micron-scale microscopy techniques; computer simulations emphasize a highly multi-scale approach in order to bridge between molecular and cellular scales. International collaboration between US and French groups adds complementary expertise for simulating large-scale biomolecular systems in the presence of hydrodynamic flow. The impact of the research activities is enhanced by extensive involvement of undergraduate and graduate students in highly interdisciplinary research with a strong focus on the continued recruitment and support of females and underrepresented minorities in biophysical research. The development of a new physics curriculum targeted at life science majors is another goal for making physics education more relevant for biology topics. In another direction, a public outreach component is developed where physical demonstrations are combined with computer simulations to illustrate the abstract concept of diffusion via particle interactions in the context of biology.This collaborative US/France project is supported by the US National Science Foundation and the French Agence Nationale de la Recherche, where NSF funds the US investigator and ANR funds the partners in France.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.

在生物细胞内，存在着高度浓缩的生物分子、蛋白质和核酸的混合物，它们经常相互作用。大多数这些相互作用是非特异性的，但它们仍然可能导致聚类，聚集和相分离区域的形成，所有这些都可能对生物功能产生重大影响。在该项目中，活细胞内存在的流体动力学流动被研究为一个新的维度，预计将调节瞬时分子相互作用，并因此增强或抑制聚集和相分离。这些努力的结果是一个更完整的，完全动态的生物分子如何在密集的生物环境中相互作用的观点。该项目涉及生物物理实验和计算机模拟之间的紧密结合。美国和法国团体之间的国际合作具有协同效益，可以开发互补的计算专业知识，用于在外部流动的情况下大规模模拟相互作用的生物分子。本科生和研究生广泛参与高度跨学科的研究，重点是继续招募和支持女性和代表性不足的少数群体参与生物物理研究，从而增强了研究活动的影响。针对生命科学专业的新物理课程的开发是使物理教育与生物学主题更加相关的另一个目标。在另一个方向，一个公共宣传部分是开发物理演示与计算机模拟相结合，以说明通过粒子相互作用在生物学的背景下扩散的抽象概念。在密集的细胞环境中，生物分子经常通过短暂的非特异性相互作用相互作用。这种相互作用可能会导致聚集、浓缩和聚合。在这里，剪切流对这些过程的影响作为一个新的维度，对了解在现实的生物环境中的生物分子的行为进行检查。剪切流存在于生物细胞中，并且预期调节瞬时相互作用和冷凝，并潜在地促进聚集。不同的模型系统将通过实验和计算机模拟进行研究。模型系统包括球状蛋白质的浓缩溶液，研究非冷凝的瞬时聚类，肽-RNA混合物，研究冷凝，和高度动态的内在无序肽，以研究拥挤和冷凝环境中的分子内和分子间扩散。实验涉及纳米尺度的光谱学和微米尺度的显微镜技术;计算机模拟强调高度多尺度的方法，以便在分子和细胞尺度之间架起桥梁。美国和法国集团之间的国际合作增加了在流体动力学流动存在下模拟大规模生物分子系统的补充专业知识。本科生和研究生广泛参与高度跨学科的研究，重点是继续招募和支持女性和代表性不足的少数群体参与生物物理研究，从而增强了研究活动的影响。针对生命科学专业的新物理课程的开发是使物理教育与生物学主题更加相关的另一个目标。在另一个方向上，开发了一个公共外展组件，其中物理演示与计算机模拟相结合，以说明生物学背景下通过粒子相互作用扩散的抽象概念。这个美国/法国合作项目得到美国国家科学基金会和法国国家研究机构的支持，其中NSF资助美国调查员，ANR资助法国的合作伙伴。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。

项目成果

Modeling Concentration-dependent Phase Separation Processes Involving Peptides and RNA via Residue-Based Coarse-Graining

通过基于残基的粗粒度对涉及肽和 RNA 的浓度依赖性相分离过程进行建模

• DOI: 10.1021/acs.jctc.2c00856
• 发表时间: 2023
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Valdes-Garcia, Gilberto;Heo, Lim;Lapidus, Lisa J.;Feig, Michael
• 通讯作者: Feig, Michael

The effect of polymer length in liquid-liquid phase separation

• DOI: 10.1016/j.xcrp.2023.101415
• 发表时间: 2023-05
• 期刊: Cell reports. Physical science
• 作者: Gilberto Valdés-García;Kasun Gamage;Casey R. Smith;K. Martirosova;M. Feig;Lisa J. Lapidus

One bead per residue can describe all-atom protein structures.

• DOI: 10.1016/j.str.2023.10.013
• 发表时间: 2023-11
• 期刊: Structure
• 影响因子: 5.7
• 作者: Lim Heo;M. Feig