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An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes
BACKGROUND: The power and simplicity of visual colony counting have made it the mainstay of microbiological analysis for more than 130 years. A disadvantage of the method is the long time required to generate visible colonies from cells in a sample. New rapid testing technologies generally have fail...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2798718/ https://www.ncbi.nlm.nih.gov/pubmed/20062794 http://dx.doi.org/10.1371/journal.pone.0008609 |
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author | London, Roanna Schwedock, Julie Sage, Andrew Valley, Heather Meadows, Jamie Waddington, Michael Straus, Don |
author_facet | London, Roanna Schwedock, Julie Sage, Andrew Valley, Heather Meadows, Jamie Waddington, Michael Straus, Don |
author_sort | London, Roanna |
collection | PubMed |
description | BACKGROUND: The power and simplicity of visual colony counting have made it the mainstay of microbiological analysis for more than 130 years. A disadvantage of the method is the long time required to generate visible colonies from cells in a sample. New rapid testing technologies generally have failed to maintain one or more of the major advantages of culture-based methods. PRINCIPAL FINDINGS: We present a new technology and platform that uses digital imaging of cellular autofluorescence to detect and enumerate growing microcolonies many generations before they become visible to the eye. The data presented demonstrate that the method preserves the viability of the microcolonies it detects, thus enabling generation of pure cultures for microbial identification. While visual colony counting detects Escherichia coli colonies containing about 5×10(6) cells, the new imaging method detects E. coli microcolonies when they contain about 120 cells and microcolonies of the yeast Candida albicans when they contain only about 12 cells. We demonstrate that digital imaging of microcolony autofluorescence detects a broad spectrum of prokaryotic and eukaryotic microbes and present a model for predicting the time to detection for individual strains. Results from the analysis of environmental samples from pharmaceutical manufacturing plants containing a mixture of unidentified microbes demonstrate the method's improved test turnaround times. CONCLUSION: This work demonstrates a new technology and automated platform that substantially shortens test times while maintaining key advantages of the current methods. |
format | Text |
id | pubmed-2798718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-27987182010-01-09 An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes London, Roanna Schwedock, Julie Sage, Andrew Valley, Heather Meadows, Jamie Waddington, Michael Straus, Don PLoS One Research Article BACKGROUND: The power and simplicity of visual colony counting have made it the mainstay of microbiological analysis for more than 130 years. A disadvantage of the method is the long time required to generate visible colonies from cells in a sample. New rapid testing technologies generally have failed to maintain one or more of the major advantages of culture-based methods. PRINCIPAL FINDINGS: We present a new technology and platform that uses digital imaging of cellular autofluorescence to detect and enumerate growing microcolonies many generations before they become visible to the eye. The data presented demonstrate that the method preserves the viability of the microcolonies it detects, thus enabling generation of pure cultures for microbial identification. While visual colony counting detects Escherichia coli colonies containing about 5×10(6) cells, the new imaging method detects E. coli microcolonies when they contain about 120 cells and microcolonies of the yeast Candida albicans when they contain only about 12 cells. We demonstrate that digital imaging of microcolony autofluorescence detects a broad spectrum of prokaryotic and eukaryotic microbes and present a model for predicting the time to detection for individual strains. Results from the analysis of environmental samples from pharmaceutical manufacturing plants containing a mixture of unidentified microbes demonstrate the method's improved test turnaround times. CONCLUSION: This work demonstrates a new technology and automated platform that substantially shortens test times while maintaining key advantages of the current methods. Public Library of Science 2010-01-07 /pmc/articles/PMC2798718/ /pubmed/20062794 http://dx.doi.org/10.1371/journal.pone.0008609 Text en London et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article London, Roanna Schwedock, Julie Sage, Andrew Valley, Heather Meadows, Jamie Waddington, Michael Straus, Don An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes |
title | An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes |
title_full | An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes |
title_fullStr | An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes |
title_full_unstemmed | An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes |
title_short | An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes |
title_sort | automated system for rapid non-destructive enumeration of growing microbes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2798718/ https://www.ncbi.nlm.nih.gov/pubmed/20062794 http://dx.doi.org/10.1371/journal.pone.0008609 |
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