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The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems
Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4040452/ https://www.ncbi.nlm.nih.gov/pubmed/24917858 http://dx.doi.org/10.3389/fmicb.2014.00265 |
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author | Besmer, Michael D. Weissbrodt, David G. Kratochvil, Bradley E. Sigrist, Jürg A. Weyland, Mathias S. Hammes, Frederik |
author_facet | Besmer, Michael D. Weissbrodt, David G. Kratochvil, Bradley E. Sigrist, Jürg A. Weyland, Mathias S. Hammes, Frederik |
author_sort | Besmer, Michael D. |
collection | PubMed |
description | Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab sampling hampers accurate characterization and subsequent understanding of microbial dynamics in all of these ecosystems. A logic technological progression is high throughput and full automation of the sampling, staining, measurement, and data analysis steps. Here we assess the feasibility and applicability of automated FCM by means of actual data sets produced with prototype instrumentation. As proof-of-concept we demonstrate examples of microbial dynamics in (i) flowing tap water from a municipal drinking water supply network and (ii) river water from a small creek subject to two rainfall events. In both cases, automated measurements were done at 15-min intervals during 12–14 consecutive days, yielding more than 1000 individual data points for each ecosystem. The extensive data sets derived from the automated measurements allowed for the establishment of baseline data for each ecosystem, as well as for the recognition of daily variations and specific events that would most likely be missed (or miss-characterized) by infrequent sampling. In addition, the online FCM data from the river water was combined and correlated with online measurements of abiotic parameters, showing considerable potential for a better understanding of cause-and-effect relationships in aquatic ecosystems. Although several challenges remain, the successful operation of an automated online FCM system and the basic interpretation of the resulting data sets represent a breakthrough toward the eventual establishment of fully automated online microbiological monitoring technologies. |
format | Online Article Text |
id | pubmed-4040452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40404522014-06-10 The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems Besmer, Michael D. Weissbrodt, David G. Kratochvil, Bradley E. Sigrist, Jürg A. Weyland, Mathias S. Hammes, Frederik Front Microbiol Microbiology Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab sampling hampers accurate characterization and subsequent understanding of microbial dynamics in all of these ecosystems. A logic technological progression is high throughput and full automation of the sampling, staining, measurement, and data analysis steps. Here we assess the feasibility and applicability of automated FCM by means of actual data sets produced with prototype instrumentation. As proof-of-concept we demonstrate examples of microbial dynamics in (i) flowing tap water from a municipal drinking water supply network and (ii) river water from a small creek subject to two rainfall events. In both cases, automated measurements were done at 15-min intervals during 12–14 consecutive days, yielding more than 1000 individual data points for each ecosystem. The extensive data sets derived from the automated measurements allowed for the establishment of baseline data for each ecosystem, as well as for the recognition of daily variations and specific events that would most likely be missed (or miss-characterized) by infrequent sampling. In addition, the online FCM data from the river water was combined and correlated with online measurements of abiotic parameters, showing considerable potential for a better understanding of cause-and-effect relationships in aquatic ecosystems. Although several challenges remain, the successful operation of an automated online FCM system and the basic interpretation of the resulting data sets represent a breakthrough toward the eventual establishment of fully automated online microbiological monitoring technologies. Frontiers Media S.A. 2014-06-02 /pmc/articles/PMC4040452/ /pubmed/24917858 http://dx.doi.org/10.3389/fmicb.2014.00265 Text en Copyright © 2014 Besmer, Weissbrodt, Kratochvil, Sigrist, Weyland and Hammes. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Besmer, Michael D. Weissbrodt, David G. Kratochvil, Bradley E. Sigrist, Jürg A. Weyland, Mathias S. Hammes, Frederik The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
title | The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
title_full | The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
title_fullStr | The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
title_full_unstemmed | The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
title_short | The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
title_sort | feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4040452/ https://www.ncbi.nlm.nih.gov/pubmed/24917858 http://dx.doi.org/10.3389/fmicb.2014.00265 |
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