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Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system
The bacterial foodborne pathogen Listeria monocytogenes has been implicated in fresh produce outbreaks with a significant economic impact. Given that L. monocytogenes is widespread in the environment, food production facilities constantly monitor for the presence of Listeria species. To develop a su...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289798/ https://www.ncbi.nlm.nih.gov/pubmed/34076739 http://dx.doi.org/10.1007/s00203-021-02388-2 |
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author | Quiñones, Beatriz Yambao, Jaszemyn C. De Guzman, Veronica S. Lee, Bertram G. Medin, David L. |
author_facet | Quiñones, Beatriz Yambao, Jaszemyn C. De Guzman, Veronica S. Lee, Bertram G. Medin, David L. |
author_sort | Quiñones, Beatriz |
collection | PubMed |
description | The bacterial foodborne pathogen Listeria monocytogenes has been implicated in fresh produce outbreaks with a significant economic impact. Given that L. monocytogenes is widespread in the environment, food production facilities constantly monitor for the presence of Listeria species. To develop a surveillance platform for food processing facilities, this study conducted a comparative genomic analysis for the identification of conserved high copy sequences in the ribosomal RNA of Listeria species. Simulated folding was performed to assess RNA accessibility in the identified genomic regions targeted for detection, and the developed singleplex assay accurately detected cell amounts lower than 5 cells, while no signals were detected for non-targeted bacteria. The singleplex assay was subsequently tested with a flow-through system, consisting of a DNA aptamer-capture step, followed by sample concentration and mechanical lysis for the detection of Listeria species. Validation experiments indicated the continuous flow-through system accurately detected Listeria species at low cell concentrations. |
format | Online Article Text |
id | pubmed-8289798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-82897982021-08-05 Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system Quiñones, Beatriz Yambao, Jaszemyn C. De Guzman, Veronica S. Lee, Bertram G. Medin, David L. Arch Microbiol Original Paper The bacterial foodborne pathogen Listeria monocytogenes has been implicated in fresh produce outbreaks with a significant economic impact. Given that L. monocytogenes is widespread in the environment, food production facilities constantly monitor for the presence of Listeria species. To develop a surveillance platform for food processing facilities, this study conducted a comparative genomic analysis for the identification of conserved high copy sequences in the ribosomal RNA of Listeria species. Simulated folding was performed to assess RNA accessibility in the identified genomic regions targeted for detection, and the developed singleplex assay accurately detected cell amounts lower than 5 cells, while no signals were detected for non-targeted bacteria. The singleplex assay was subsequently tested with a flow-through system, consisting of a DNA aptamer-capture step, followed by sample concentration and mechanical lysis for the detection of Listeria species. Validation experiments indicated the continuous flow-through system accurately detected Listeria species at low cell concentrations. Springer Berlin Heidelberg 2021-06-02 2021 /pmc/articles/PMC8289798/ /pubmed/34076739 http://dx.doi.org/10.1007/s00203-021-02388-2 Text en © This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Quiñones, Beatriz Yambao, Jaszemyn C. De Guzman, Veronica S. Lee, Bertram G. Medin, David L. Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system |
title | Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system |
title_full | Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system |
title_fullStr | Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system |
title_full_unstemmed | Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system |
title_short | Genomic analysis of high copy-number sequences for the targeted detection of Listeria species using a flow-through surveillance system |
title_sort | genomic analysis of high copy-number sequences for the targeted detection of listeria species using a flow-through surveillance system |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289798/ https://www.ncbi.nlm.nih.gov/pubmed/34076739 http://dx.doi.org/10.1007/s00203-021-02388-2 |
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