Digital E. coli Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of E. coli from Water Samples
Tashkandi, Nouran Abdulatif
De Oliveira Filho, José Ilton
Oviedo-Osornio, Claudia Iluhí
Danish, Muhammad S.
Salama, Khaled N.
KAUST DepartmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Electrical and Computer Engineering Program
Electrical and Computer Engineering
Water Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 239455-6900, Saudi Arabia.
Environmental Science and Engineering Program
Water Desalination and Reuse Research Center (WDRC)
Biological and Environmental Science and Engineering (BESE) Division
KAUST Grant NumberREI/1/4178-03-01
Permanent link to this recordhttp://hdl.handle.net/10754/674957
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AbstractBiological water contamination detection-based assays are essential to test water quality; however, these assays are prone to false-positive results and inaccuracies, are time-consuming, and use complicated procedures to test large water samples. Herein, we show a simple detection and counting method for E. coli in the water samples involving a combination of DNAzyme sensor, microfluidics, and computer vision strategies. We first isolated E. coli into individual droplets containing a DNAzyme mixture using droplet microfluidics. Upon bacterial cell lysis by heating, the DNAzyme mixture reacted with a particular substrate present in the crude intracellular material (CIM) of E. coli. This event triggers the dissociation of the fluorophore-quencher pair present in the DNAzyme mixture leading to a fluorescence signal, indicating the presence of E. coli in the droplets. We developed an algorithm using computer vision to analyze the fluorescent droplets containing E. coli in the presence of non-fluorescent droplets. The algorithm can detect and count fluorescent droplets representing the number of E. coli present in the sample. Finally, we show that the developed method is highly specific to detect and count E. coli in the presence of other bacteria present in the water sample.
CitationRauf, S., Tashkandi, N., de Oliveira Filho, J. I., Oviedo-Osornio, C. I., Danish, M. S., Hong, P.-Y., & Salama, K. N. (2022). Digital E. coli Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of E. coli from Water Samples. Biosensors, 12(1), 34. doi:10.3390/bios12010034
SponsorsWe acknowledge the financial support from King Abdullah University of Science and Technology (KAUST), Saudi Arabia. K.N. Salama would like to acknowledge the funding from AMPM center under the CCF grant. K.N. Salama and Pei-Ying Hong would like to acknowledge the CoE NEOM Research grant REI/1/4178-03-01.
CollectionsArticles; Biological and Environmental Science and Engineering (BESE) Division; Environmental Science and Engineering Program; Electrical and Computer Engineering Program; Water Desalination and Reuse Research Center (WDRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
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