TY - JOUR
T1 - Digital E. coli Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of E. coli from Water Samples
AU - Rauf, Sakandar
AU - Tashkandi, Nouran Abdulatif
AU - De Oliveira Filho, José Ilton
AU - Oviedo-Osornio, Claudia Iluhí
AU - Danish, Muhammad S.
AU - Hong, Pei-Ying
AU - Salama, Khaled N.
N1 - KAUST Repository Item: Exported on 2022-01-18
Acknowledged KAUST grant number(s): REI/1/4178-03-01
Acknowledgements: We 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.
PY - 2022/1/10
Y1 - 2022/1/10
N2 - Biological 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.
AB - Biological 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.
UR - http://hdl.handle.net/10754/674957
UR - https://www.mdpi.com/2079-6374/12/1/34
U2 - 10.3390/bios12010034
DO - 10.3390/bios12010034
M3 - Article
C2 - 35049662
SN - 2079-6374
VL - 12
SP - 34
JO - Biosensors
JF - Biosensors
IS - 1
ER -