Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water
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...
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sg-ntu-dr.10356-800422023-07-14T15:57:05Z Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water Golberg, Alexander Linshiz, Gregory Kravets, Ilia Stawski, Nina Hillson, Nathan J. Yarmush, Martin L. Marks, Robert S. Konry, Tania Brody, James P. School of Materials Science & Engineering DRNTU::Engineering::Computer science and engineering 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. Published version 2014-06-10T03:21:11Z 2019-12-06T13:39:18Z 2014-06-10T03:21:11Z 2019-12-06T13:39:18Z 2014 2014 Journal Article Golberg, A., Linshiz, G., Kravets, I., Stawski, N., Hillson, N. J., Yarmush, M. L., et al. (2014). Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water. PLoS ONE, 9(1), e86341-. 1932-6203 https://hdl.handle.net/10356/80042 http://hdl.handle.net/10220/19607 10.1371/journal.pone.0086341 24475107 en PLoS ONE © 2014 Golberg et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. application/pdf |
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DRNTU::Engineering::Computer science and engineering 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 |
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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. |
author2 |
Brody, James P. |
author_facet |
Brody, James P. Golberg, Alexander Linshiz, Gregory Kravets, Ilia Stawski, Nina Hillson, Nathan J. Yarmush, Martin L. Marks, Robert S. Konry, Tania |
format |
Article |
author |
Golberg, Alexander Linshiz, Gregory Kravets, Ilia Stawski, Nina Hillson, Nathan J. Yarmush, Martin L. Marks, Robert S. Konry, Tania |
author_sort |
Golberg, Alexander |
title |
Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water |
title_short |
Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water |
title_full |
Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water |
title_fullStr |
Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water |
title_full_unstemmed |
Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water |
title_sort |
cloud-enabled microscopy and droplet microfluidic platform for specific detection of escherichia coli in water |
publishDate |
2014 |
url |
https://hdl.handle.net/10356/80042 http://hdl.handle.net/10220/19607 |
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1773551211001151488 |