Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples
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 metho...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Biosensors |
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| Online Access: | https://www.mdpi.com/2079-6374/12/1/34 |
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| author | Sakandar Rauf Nouran Tashkandi José Ilton de Oliveira Filho Claudia Iluhí Oviedo-Osornio Muhammad S. Danish Pei-Ying Hong Khaled N. Salama |
| author_facet | Sakandar Rauf Nouran Tashkandi José Ilton de Oliveira Filho Claudia Iluhí Oviedo-Osornio Muhammad S. Danish Pei-Ying Hong Khaled N. Salama |
| author_sort | Sakandar Rauf |
| collection | DOAJ |
| description | 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 <i>E. coli</i> in the water samples involving a combination of DNAzyme sensor, microfluidics, and computer vision strategies. We first isolated <i>E. coli</i> 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 <i>E. coli</i>. This event triggers the dissociation of the fluorophore-quencher pair present in the DNAzyme mixture leading to a fluorescence signal, indicating the presence of <i>E. coli</i> in the droplets. We developed an algorithm using computer vision to analyze the fluorescent droplets containing <i>E. coli</i> in the presence of non-fluorescent droplets. The algorithm can detect and count fluorescent droplets representing the number of <i>E. coli</i> present in the sample. Finally, we show that the developed method is highly specific to detect and count <i>E. coli</i> in the presence of other bacteria present in the water sample. |
| first_indexed | 2024-03-10T01:49:37Z |
| format | Article |
| id | doaj.art-fa4a0225a9624245be1ab46492ecc190 |
| institution | Directory Open Access Journal |
| issn | 2079-6374 |
| language | English |
| last_indexed | 2024-03-10T01:49:37Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj.art-fa4a0225a9624245be1ab46492ecc1902023-11-23T13:08:18ZengMDPI AGBiosensors2079-63742022-01-011213410.3390/bios12010034Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water SamplesSakandar Rauf0Nouran Tashkandi1José Ilton de Oliveira Filho2Claudia Iluhí Oviedo-Osornio3Muhammad S. Danish4Pei-Ying Hong5Khaled N. Salama6Sensors Laboratory, Advanced Membranes & Porous Materials Centre (AMPMC), Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi ArabiaSensors Laboratory, Advanced Membranes & Porous Materials Centre (AMPMC), Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi ArabiaSensors Laboratory, Advanced Membranes & Porous Materials Centre (AMPMC), Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi ArabiaWater Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 239455-6900, Saudi ArabiaDepartment of Computer Science, Information Technology University (ITU), Arfa Software Technology Park, Lahore 40050, PakistanWater Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 239455-6900, Saudi ArabiaSensors Laboratory, Advanced Membranes & Porous Materials Centre (AMPMC), Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi ArabiaBiological 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 <i>E. coli</i> in the water samples involving a combination of DNAzyme sensor, microfluidics, and computer vision strategies. We first isolated <i>E. coli</i> 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 <i>E. coli</i>. This event triggers the dissociation of the fluorophore-quencher pair present in the DNAzyme mixture leading to a fluorescence signal, indicating the presence of <i>E. coli</i> in the droplets. We developed an algorithm using computer vision to analyze the fluorescent droplets containing <i>E. coli</i> in the presence of non-fluorescent droplets. The algorithm can detect and count fluorescent droplets representing the number of <i>E. coli</i> present in the sample. Finally, we show that the developed method is highly specific to detect and count <i>E. coli</i> in the presence of other bacteria present in the water sample.https://www.mdpi.com/2079-6374/12/1/34DNAzyme<i>E. coli</i>microfluidicswater qualityfluorescence detectioncomputer vision |
| spellingShingle | Sakandar Rauf Nouran Tashkandi José Ilton de Oliveira Filho Claudia Iluhí Oviedo-Osornio Muhammad S. Danish Pei-Ying Hong Khaled N. Salama Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples Biosensors DNAzyme <i>E. coli</i> microfluidics water quality fluorescence detection computer vision |
| title | Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples |
| title_full | Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples |
| title_fullStr | Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples |
| title_full_unstemmed | Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples |
| title_short | Digital <i>E. coli</i> Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of <i>E. coli</i> from Water Samples |
| title_sort | digital i e coli i counter a microfluidics and computer vision based dnazyme method for the isolation and specific detection of i e coli i from water samples |
| topic | DNAzyme <i>E. coli</i> microfluidics water quality fluorescence detection computer vision |
| url | https://www.mdpi.com/2079-6374/12/1/34 |
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