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| Content Provider | Directory of Open Access Journals (DOAJ) |
|---|---|
| Author | Xu Yang Nicharee Wisuthiphaet Glenn M. Young Nitin Nitin |
| Abstract | Rapid detection of bacterial pathogens is a critical unmet need for both food and environmental samples such as irrigation water. As a part of the Food safety Modernization Act (FSMA), The Produce Safety rule has established several requirements for testing for the presence of generic Escherichia coli in water, but the current method available for testing (EPA M1603) demands specified multiple colony verification and highly trained personnel to perform these tests. The purpose of the study was to assess a phage induced bacterial lysis using quantitative image analysis to achieve rapid detection of E. coli at low concentrations within 8 hours. This study aimed to develop a simple yet highly sensitive and specific approach to detect target bacteria in complex matrices. In the study, E. coli cells were first enriched in tryptic soy broth (TSB), followed by T7 phage induced lysis, concentration, staining and fluorescent imaging. Image analysis was conducted including image pre-processing, image segmentation and quantitatively analysis of cellular morphological features (area, eccentricity and full width at half maximum). Challenge experiments using realistic matrices, including simulated fresh produce wash water, coconut water and spinach wash water, demonstrated the method can be applied for use in situations that occur in food processing facilities. The results indicated E. coli cells that are lysed by T7 phages demonstrated significantly (P < 0.05) higher extracellular DNA release, altered cellular shape (from rod to circular) and diffused fluorescent signal intensity. Using this biosensing strategy, a sensitivity to detect Escherichia coli at 10 CFU/ml within 8 hours was achieved, both in laboratory medium and in complex matrices. The proposed phage based biosensing strategy enables rapid detection of bacteria and is applicable to analysis of food systems. Furthermore, the steps involved in this assay can be automated to enable detection of target bacteria in food facilities without extensive resources. |
| e-ISSN | 19326203 |
| DOI | 10.1371/journal.pone.0233853 |
| Journal | PLoS ONE |
| Issue Number | 6 |
| Volume Number | 15 |
| Language | English |
| Publisher | Public Library of Science (PLoS) |
| Publisher Date | 2020-01-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Medicine Science |
| Content Type | Text |
| Resource Type | Article |
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