Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water
Abstract
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.
- Authors:
-
- Harvard Medical School, Boston, MA (United States). Shriners Burns Inst. Massachusetts General Hospital. Centre for Engineering in Medicine
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States). Fuels Synthesis Division; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical BioSciences Division; USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
- Technion-Israel Inst. of Technology, Haifa (Israel). Dept. of Computer Science
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States). Fuels Synthesis Division; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical BioSciences Division
- Harvard Medical School, Boston, MA (United States). Shriners Burns Inst. Massachusetts General Hospital. Centre for Engineering in Medicine; Rutgers Univ., New Brunswick, NJ (United States). Dept. of Biomedical Engineering
- Ben-Gurion Univ. of the Negev, Beer-Sheva (Israel). The National Inst. of Biotechnology in Negev. Dept. of Biotechnology Engineering; Nanyang Technological Univ. (Singapore). School of Materials Science and Engineering; NRF CREATE program for Nanomaterials in Energy and Water Management (Singapore)
- Northeastern Univ., Boston, MA (United States). Dept. of Pharmaceutical Sciences. School of Pharmacy. Bouvé College of Health Sciences
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); Shriners Foundation; Singapore National Research Foundation
- OSTI Identifier:
- 1511391
- Grant/Contract Number:
- AC02-05CH11231; 85120-BOS
- Resource Type:
- Accepted Manuscript
- Journal Name:
- PLoS ONE
- Additional Journal Information:
- Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 1932-6203
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; microfluidics; water resources; polymerase chain reaction; water pollution; water quality; fluorescence microscopy; fluorescence imaging; water management
Citation Formats
Golberg, Alexander, Linshiz, Gregory, Kravets, Ilia, Stawski, Nina, Hillson, Nathan J., Yarmush, Martin L., Marks, Robert S., and Konry, Tania. Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water. United States: N. p., 2014.
Web. doi:10.1371/journal.pone.0086341.
Golberg, Alexander, Linshiz, Gregory, Kravets, Ilia, Stawski, Nina, Hillson, Nathan J., Yarmush, Martin L., Marks, Robert S., & Konry, Tania. Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water. United States. https://doi.org/10.1371/journal.pone.0086341
Golberg, Alexander, Linshiz, Gregory, Kravets, Ilia, Stawski, Nina, Hillson, Nathan J., Yarmush, Martin L., Marks, Robert S., and Konry, Tania. Mon .
"Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water". United States. https://doi.org/10.1371/journal.pone.0086341. https://www.osti.gov/servlets/purl/1511391.
@article{osti_1511391,
title = {Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water},
author = {Golberg, Alexander and Linshiz, Gregory and Kravets, Ilia and Stawski, Nina and Hillson, Nathan J. and Yarmush, Martin L. and Marks, Robert S. and Konry, Tania},
abstractNote = {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.},
doi = {10.1371/journal.pone.0086341},
journal = {PLoS ONE},
number = 1,
volume = 9,
place = {United States},
year = {Mon Jan 27 00:00:00 EST 2014},
month = {Mon Jan 27 00:00:00 EST 2014}
}
Web of Science
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