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.
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;Department of Computer Science, Technion Institute of Technology, Haifa, Israel;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;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;Centre for Engineering in Medicine, Massachusetts General Hospital, Harvard Medical School, Shriners Burns Institute, Boston, Massachusetts, United States of America;Department of Biomedical Engineering, Rutgers University, New Jersey, United States of America;Department of Biotechnology Engineering, The National Institute of Biotechnology in Negev, Ben Gurion University, Beer-Sheva, Israel;School of Materials Science and Engineering, Nanyang Technological University, Singapore;NRF CREATE program for Nanomaterials in Energy and Water Management, Singapore;Department of Pharmaceutical Sciences, School of Pharmacy Bouvé College of Health Sciences, Northeastern University, Boston, Massachusetts, United States of America
Recommended Citation:
Alexander Golberg,Gregory Linshiz,Ilia Kravets,et al. Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water[J]. PLOS ONE,2014-01-01,9(1)