Cargando…
Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature
A novel imaging-driven technique with an integrated fluorescence signature to enable automated enumeration of two species of cyanobacteria and an alga of somewhat similar morphology to one of the cyanobacteria is presented to demonstrate proof-of-concept that high accuracy, imaging-based, rapid wate...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998128/ https://www.ncbi.nlm.nih.gov/pubmed/29899430 http://dx.doi.org/10.1038/s41598-018-27406-0 |
_version_ | 1783331187856506880 |
---|---|
author | Jin, Chao Mesquita, Maria M. F. Deglint, Jason L. Emelko, Monica B. Wong, Alexander |
author_facet | Jin, Chao Mesquita, Maria M. F. Deglint, Jason L. Emelko, Monica B. Wong, Alexander |
author_sort | Jin, Chao |
collection | PubMed |
description | A novel imaging-driven technique with an integrated fluorescence signature to enable automated enumeration of two species of cyanobacteria and an alga of somewhat similar morphology to one of the cyanobacteria is presented to demonstrate proof-of-concept that high accuracy, imaging-based, rapid water quality analysis can be with conventional equipment available in typical water quality laboratories-this is not currently available. The results presented herein demonstrate that the developed method identifies and enumerates cyanobacterial cells at a level equivalent to or better than that achieved using standard manual microscopic enumeration techniques, but in less time, and requiring significantly fewer resources. When compared with indirect measurement methods, the proposed method provides better accuracy at both low and high cell concentrations. It extends the detection range for cell enumeration while maintaining accuracy and increasing enumeration speed. The developed method not only accurately estimates cell concentrations, but it also reliably distinguishes between cells of Anabaena flos-aquae, Microcystis aeruginosa, and Ankistrodesmus in mixed cultures by taking advantage of additional contrast between the target cell and complex background gained under fluorescent light. Thus, the proposed image-driven approach offers promise as a robust and cost-effective tool for identifying and enumerating microscopic cells based on their unique morphological features. |
format | Online Article Text |
id | pubmed-5998128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59981282018-06-21 Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature Jin, Chao Mesquita, Maria M. F. Deglint, Jason L. Emelko, Monica B. Wong, Alexander Sci Rep Article A novel imaging-driven technique with an integrated fluorescence signature to enable automated enumeration of two species of cyanobacteria and an alga of somewhat similar morphology to one of the cyanobacteria is presented to demonstrate proof-of-concept that high accuracy, imaging-based, rapid water quality analysis can be with conventional equipment available in typical water quality laboratories-this is not currently available. The results presented herein demonstrate that the developed method identifies and enumerates cyanobacterial cells at a level equivalent to or better than that achieved using standard manual microscopic enumeration techniques, but in less time, and requiring significantly fewer resources. When compared with indirect measurement methods, the proposed method provides better accuracy at both low and high cell concentrations. It extends the detection range for cell enumeration while maintaining accuracy and increasing enumeration speed. The developed method not only accurately estimates cell concentrations, but it also reliably distinguishes between cells of Anabaena flos-aquae, Microcystis aeruginosa, and Ankistrodesmus in mixed cultures by taking advantage of additional contrast between the target cell and complex background gained under fluorescent light. Thus, the proposed image-driven approach offers promise as a robust and cost-effective tool for identifying and enumerating microscopic cells based on their unique morphological features. Nature Publishing Group UK 2018-06-13 /pmc/articles/PMC5998128/ /pubmed/29899430 http://dx.doi.org/10.1038/s41598-018-27406-0 Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jin, Chao Mesquita, Maria M. F. Deglint, Jason L. Emelko, Monica B. Wong, Alexander Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
title | Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
title_full | Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
title_fullStr | Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
title_full_unstemmed | Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
title_short | Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
title_sort | quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998128/ https://www.ncbi.nlm.nih.gov/pubmed/29899430 http://dx.doi.org/10.1038/s41598-018-27406-0 |
work_keys_str_mv | AT jinchao quantificationofcyanobacterialcellsviaanovelimagingdriventechniquewithanintegratedfluorescencesignature AT mesquitamariamf quantificationofcyanobacterialcellsviaanovelimagingdriventechniquewithanintegratedfluorescencesignature AT deglintjasonl quantificationofcyanobacterialcellsviaanovelimagingdriventechniquewithanintegratedfluorescencesignature AT emelkomonicab quantificationofcyanobacterialcellsviaanovelimagingdriventechniquewithanintegratedfluorescencesignature AT wongalexander quantificationofcyanobacterialcellsviaanovelimagingdriventechniquewithanintegratedfluorescencesignature |