Ultrahigh-Throughput Single-Molecule Spectroscopy and Multidimensional Super-Resolution Microscopy

在化学系化学测量和成像（CMI）项目的支持下，加州大学伯克利分校的徐克教授和他的研究小组正在开发用于单分子光谱和多维超分辨率显微镜的超高通量方法。超分辨率显微镜在过去十年中的兴起彻底改变了研究人员在纳米尺度上研究化学，生物和材料系统的方式。该项目将超分辨率显微镜扩展到高维测量，以便在单分子水平上实现化学成像的新能力。新方法包括使用可膨胀水凝胶来控制扩散，结合微流体技术，以及应用机器学习方法来分析高通量测量的数据。这项研究所实现的测量有可能揭示有关单分子行为的新知识，并提供新的工具和概念，从根本上使不同的研究领域受益。此外，该项目还为学生提供现代实验技术和大数据分析方法方面的高级培训，这些技术和方法在学术界和工业界都是越来越重要的就业技能。该项目还支持徐教授通过他的教学、指导和外展活动提供一个包容的环境。基于单分子荧光检测的超分辨率显微镜的兴起，通常被称为单分子定位显微镜（SMLM），在过去十年中彻底改变了化学、生物和材料系统的研究。在该项目中，徐教授领导的研究团队正在开发新的实验方法，以实现单分子特性的高维和高通量测量，以扩展SMLM的能力。除了利用可膨胀水凝胶和微流体技术记录大量单分子的扩散速率和荧光光谱的实验方法外，该团队还致力于应用机器学习算法来分析来自超高通量单分子光谱测量的数据。通过整合这些不同的技术，该项目旨在提供高的时间分辨率，用于记录未束缚的单分子的快速动力学，以便从单分子图像中提取高维分子信息，用于超分辨率映射，并阐明大分子扩散中的尺寸效应。这项工作的更广泛影响包括在广泛的研究领域中超高通量和多维单分子测量的潜在应用。参与该项目的学生还获得了基于新知识、工具和正在开发的概念的宝贵的跨学科培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the Chemical Measurement and Imaging (CMI) Program in the Division of Chemistry, Professor Ke Xu and his research group at the University of California-Berkeley are developing ultrahigh-throughput approaches for single-molecule spectroscopy and multidimensional super-resolution microscopy. The rise of super-resolution microscopy over the past decade has revolutionized how researchers study chemical, biological, and materials systems at the nanometer scale. This project extends super-resolution microscopy to high-dimensional measurements in order to enable new capabilities for chemical imaging at the single-molecule level. New approaches include the use of expandable hydrogels to control diffusion, incorporation of microfluidic techniques, and the application of machine learning approaches to analyze data from the high-throughput measurements. The measurements enabled by this research have the potential to reveal new knowledge about the behavior of single molecules and to provide new tools and concepts that will benefit diverse research fields in fundamental ways. Moreover, the project provides advanced student training in modern experimental technologies and big-data analysis methods that are increasingly important skills for employment in both academia and industry. The project also supports Professor Xu in providing an inclusive environment through his commitment to teaching, mentoring, and outreach activities.The rise of super-resolution microscopy based on the detection of single-molecule fluorescence, often known as single-molecule localization microscopy (SMLM), has revolutionized the study of chemical, biological, and materials systems over the past decade. In this project, the research team led by Professor Xu is developing new experimental approaches to enable high-dimensional and high-throughput measurements of single-molecule properties in order to expand the capabilities of SMLM. In addition to experimental approaches that take advantage of expandable hydrogels and microfluidic techniques to record diffusion rates and fluorescence spectra for a very large number of single molecules, the team is also working to apply machine learning algorithms to analyze the data from the ultrahigh-throughput single-molecule spectroscopy measurements for millions of molecules. Through the integration of these diverse techniques, the project aims to provide high temporal resolution for recording the fast dynamics of untethered single molecules, to enable the extraction of high-dimensional molecular information from single-molecule images for super-resolution mapping, and to elucidate size effects in macromolecule diffusion. Broader impacts of the work include potential applications of ultrahigh-throughput and multidimensional single-molecule measurements across a wide range of research areas. Students working on the project also gain valuable cross-disciplinary training based on the new knowledge, tools, and concepts that are being developed.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.