CAREER: Multiplex microfluidic and automation tools for neurogenetics and live imaging

职业：用于神经遗传学和实时成像的多重微流体和自动化工具

• 批准号: 0954578
• 负责人: Hang Lu
• 金额: $ 40.05万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0954578&HistoricalAwards=false
• 关键词: CAREER; Multiplex; microfluidic; automation; tools

0954578LuThe long-term objective is to develop and use powerful microfluidic and automation tools to understand genetic pathways that regulate the biochemical communications between neurons and other tissues in C. elegans. Microfluidics is ideal for studies of small organisms such as C. elegans because of the relevant length scales and the possibility of integration and automation. The research objective of the CAREER project is to engineer a microfluidic system for live imaging of dynamic processes in vivo, to accomplish automated image processing, and to identify roles of genes in neuronal biochemical communications.This system will significantly increase the throughput and accuracy of in vivo live imaging experiments in model organisms. It streamlines and automates the painstakingly manual procedure of microscopy, in some cases enables some experiments that are otherwise impossible to do, and reduces the noise and artifacts in these experiments. The image analysis algorithms will provide quantitative data with large throughput to allow good statistics. The approach is innovative because the technologies developed here dramatically increase the capabilities and throughput of current assay tools, enabling key biological experiments that are not currently performed. Furthermore, the technology is broadly applicable to other biological systems and could potentially lead to new therapeutics for related diseases.

0954578长期目标是开发和使用强大的微流体和自动化工具来了解调节秀丽隐杆线虫中神经元与其他组织之间生化通信的遗传途径。由于相关的长度尺度以及整合和自动化的可能性，微流体非常适合对秀丽隐杆线虫等小生物的研究。职业项目的研究目标是设计一种微流体系统，用于体内动态过程的实时成像，完成自动图像处理，并确定基因在神经元生物化学通信中的作用。该系统将大大提高模型生物体中体内现场成像实验的吞吐量和准确性。它简化并自动化了显微镜的精心手动程序，在某些情况下可以实现一些实验，这些实验是不可能做的，并减少了这些实验中的噪声和伪影。图像分析算法将提供具有较大吞吐量的定量数据以允许良好的统计数据。这种方法具有创新性，因为这里开发的技术大大提高了当前测定工具的功能和吞吐量，从而实现了当前尚未执行的关键生物学实验。此外，该技术广泛适用于其他生物系统，并有可能导致针对相关疾病的新疗法。