Centre for Engineering in Medicine, Massachusetts General Hospital, Harvard Medical School, Shriners Burns Institute, Boston, Massachusetts, United States of America.
Fuels Synthesis Division, Joint BioEnergy Institute, Emeryville, California, United States of America ; Physical BioSciences Division, Lawrence Berkeley National Labs, Berkeley, California, United States of America ; DOE Joint Genome Institute, Walnut Creek, California, United States of America.
PLoS One. 2014 Jan 27;9(1):e86341. doi: 10.1371/journal.pone.0086341. eCollection 2014.
We report an all-in-one platform - ScanDrop - for the rapid and specific capture, detection, and identification of bacteria in drinking water. The ScanDrop platform integrates droplet microfluidics, a portable imaging system, and cloud-based control software and data storage. The cloud-based control software and data storage enables robotic image acquisition, remote image processing, and rapid data sharing. These features form a "cloud" network for water quality monitoring. We have demonstrated the capability of ScanDrop to perform water quality monitoring via the detection of an indicator coliform bacterium, Escherichia coli, in drinking water contaminated with feces. Magnetic beads conjugated with antibodies to E. coli antigen were used to selectively capture and isolate specific bacteria from water samples. The bead-captured bacteria were co-encapsulated in pico-liter droplets with fluorescently-labeled anti-E. coli antibodies, and imaged with an automated custom designed fluorescence microscope. The entire water quality diagnostic process required 8 hours from sample collection to online-accessible results compared with 2-4 days for other currently available standard detection methods.
我们报告了一个一体化平台 - ScanDrop - 用于快速和特异性地捕获、检测和识别饮用水中的细菌。ScanDrop 平台集成了液滴微流控技术、便携式成像系统以及基于云的控制软件和数据存储。基于云的控制软件和数据存储实现了机器人图像采集、远程图像处理和快速数据共享。这些功能为水质监测形成了一个“云”网络。我们通过检测粪便污染饮用水中的指示性大肠菌群来展示 ScanDrop 进行水质监测的能力。用与大肠杆菌抗原结合的抗体偶联的磁珠从水样中选择性地捕获和分离特定的细菌。将捕获的细菌与荧光标记的抗大肠杆菌抗体共包封在皮升级液滴中,并使用自动化定制荧光显微镜进行成像。与其他当前可用的标准检测方法相比,从样品采集到可在线访问结果的整个水质诊断过程仅需 8 小时。