EAGER/Collaborative Research: High-throughput, Autonomous Real-time Monitoring of Tissue Mechanical Property Change via Impedimetric Sensor Arrays

EAGER/协作研究：通过阻抗传感器阵列高通量、自主实时监测组织机械性能变化

• 批准号: 2140549
• 负责人: Shayn Peirce-Cottler
• 金额: $ 12.5万
• 依托单位: University of Virginia Main Campus
• 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 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2140549&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; throughput; Autonomous

This EArly-concept Grant for Exploratory Research (EAGER) will support research to improve engineered tissues. Engineered tissues have become important platforms for the development of therapeutics for many diseases and disorders. They hold particular promise for improving wound healing. Cells sense and respond their environment. How they sense their environment effects how they form tissues. How a cell's local environment affects it's behavior during wound healing is still not well understood. There have been substantial strides that have been made in the use of engineered tissues for disease modeling and drug development. However, simultaneously monitoring cellular behavior and tissue properties remains a challenge, and limits further advances. This project will create autonomous tissue culture monitoring platforms that enable real-time monitoring of multi-scale cellular behavior and tissue properties. If successful, scalable and high-throughput methods for autonomous monitoring of engineered tissues will be realized. This could have profound and broad socioeconomic benefits in terms of public health and drug discovery. The project will engage students through research experiences for undergraduates in data acquisition for autonomous life sciences research. The goal of this project is to advance the ability to simultaneously quantify the dynamic multi-scale attributes of engineered tissues in real time. The central approach is to establish the feasibility of a novel autonomous sensor-based experimental platform for dynamically quantifying bulk extracellular matrix (ECM) mechanical properties, multi-cellular anatomical structures, cell phenotypes, and gene and protein expression during wound healing processes using sensor-integrated 3D cell culture models. The work involves the following research objectives: 1) to utilize a cantilever sensor-integrated well plate format for autonomous monitoring of a fibroblast-Schwann cell 3D co-culture model treated with exogenous transforming growth factor (TGF-β) to invoke a wound healing response, and 2) to compare real-time changes in bulk ECM mechanical properties with temporal changes in gene and protein expression levels in 3D co-culture models. This work will yield the first quantitative description of the dynamic relationship between real-time ECM mechanical changes and cell behaviors in tissues undergoing wound healing. The project also provides research experiences for undergraduate students in data acquisition for autonomous tissue characterization and bioprocess monitoring.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.

这项早期概念探索性研究补助金 (EAGER) 将支持改善工程组织的研究。工程组织已成为开发许多疾病和病症疗法的重要平台。它们特别有希望改善伤口愈合。细胞感知并响应其环境。它们感知环境的方式会影响它们形成组织的方式。细胞的局部环境如何影响其在伤口愈合过程中的行为仍不清楚。在使用工程组织进行疾病建模和药物开发方面已经取得了实质性进展。然而，同时监测细胞行为和组织特性仍然是一个挑战，并限制了进一步的进展。该项目将创建自主组织培养监测平台，能够实时监测多尺度细胞行为和组织特性。如果成功，将实现可扩展和高通量的工程组织自主监测方法。这可能在公共卫生和药物发现方面产生深远而广泛的社会经济效益。该项目将通过本科生的研究经验吸引学生进行自主生命科学研究的数据采集。该项目的目标是提高实时同时量化工程组织的动态多尺度属性的能力。核心方法是建立一种基于新型自主传感器的实验平台的可行性，该平台可使用传感器集成的 3D 细胞培养模型动态量化大量细胞外基质 (ECM) 机械特性、多细胞解剖结构、细胞表型以及伤口愈合过程中的基因和蛋白质表达。这项工作涉及以下研究目标：1) 利用悬臂传感器集成孔板格式自动监测经外源转化生长因子 (TGF-β) 处理的成纤维细胞-雪旺细胞 3D 共培养模型以引发伤口愈合反应，2) 将批量 ECM 机械特性的实时变化与 3D 共培养中基因和蛋白质表达水平的时间变化进行比较 模型。这项工作将首次定量描述实时 ECM 机械变化与伤口愈合组织中细胞行为之间的动态关系。该项目还为本科生提供自主组织表征和生物过程监测数据采集方面的研究经验。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。