Creating an All-optical, Mechanobiology-guided, and Machine-learning-powered High-throughput Framework to Elucidate Neural Dynamics

创建全光学、机械生物学引导和机器学习驱动的高通量框架来阐明神经动力学

• 批准号: 2308574
• 负责人: Xin Tang
• 金额: $ 44.04万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-15 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2308574&HistoricalAwards=false
• 关键词: Creating; optical; Mechanobiology; guided; Machine

The ability to change cell membrane voltage is essential for neurons, nerve cells that send messages across the body. Voltage changes serve to regulate the behavior of the neuron and can be an indicator of health and disease. Like other cells in the body, neurons sense their surroundings and adapt. Current methods to study neurons often do not mimic the environments they encounter in the body and cannot measure their behavior at a high enough speed. The goal of this project is to create a new strategy that leverages advanced high-throughput microscopy and machine learning to understand neural behavior at unprecedented speeds, lower costs, and in environments that mimic those encountered in the body. Through a range of educational activities at the University of Florida, such as the Student Science Training Program (SSTP) at the Center for Precollegiate Education and Training (CPET) and Course-based Undergraduate Research Experience (CURE), this project will broaden participation of historically underserved groups in STEM fields. Training and hands-on research opportunities will be provided to all students to better prepare them for successful future careers.This project will develop and validate an experimental-computational framework that enables optical interrogation of neuron membrane voltage dynamics in a high-throughput, mechanobiology-guided, and non-invasive manner. The overarching goal is that a framework can be created by integrating wide-area voltage imaging, large tissue-mimicking hydrogel-based culture, patterned crosstalk-free optogenetic stimulation, and machine-learning powered closed-loop control to elucidate the membrane voltage dynamics of hundreds of neurons simultaneously, filling technological gaps. The project will explore novel oblique light-sheet illumination and crosstalk-free optogenetic stimulation approaches to enable exploration of plasma membrane voltage dynamics in several hundreds of neurons simultaneously. Scientific findings in this project are expected to provide a new fundamental understanding of electrophysiology and mechanobiology of neurons and inform development of new strategies to treat human diseases. The framework is scalable and can be applied to investigate other cell types, such as cardiomyocytes and muscle cells.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.

改变细胞膜电压的能力对神经元至关重要，神经元是在全身传递信息的神经细胞。电压变化有助于调节神经元的行为，可以作为健康和疾病的指标。像身体的其他细胞一样，神经元感知周围环境并适应。目前研究神经元的方法通常不能模拟它们在体内遇到的环境，也不能以足够快的速度测量它们的行为。该项目的目标是创造一种新的策略，利用先进的高通量显微镜和机器学习，以前所未有的速度、更低的成本和模拟人体环境来理解神经行为。通过佛罗里达大学的一系列教育活动，如大学预科教育和培训中心（CPET）的学生科学培训计划（SSTP）和基于课程的本科研究经验（CURE），该项目将扩大历史上服务不足的群体在STEM领域的参与。培训和实践研究的机会将提供给所有学生，以更好地为他们未来的成功职业生涯做好准备。该项目将开发并验证一个实验计算框架，该框架能够以高通量、机械生物学引导和非侵入性的方式对神经元膜电压动态进行光学询问。总体目标是，通过集成广域电压成像、大型组织模拟水凝胶培养、无串声模式光遗传刺激和机器学习驱动的闭环控制，可以创建一个框架，同时阐明数百个神经元的膜电压动态，填补技术空白。该项目将探索新的斜光片照明和无串扰光遗传刺激方法，以同时探索数百个神经元的质膜电压动态。该项目的科学发现有望为神经元的电生理学和机械生物学提供新的基础认识，并为开发治疗人类疾病的新策略提供信息。该框架是可扩展的，可用于研究其他细胞类型，如心肌细胞和肌肉细胞。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。