Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature
| Autor: | Maria M.F. Mesquita, Monica B. Emelko, Jason Deglint, Chao Jin, Alexander Wong |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Microbiological Techniques
Cyanobacteria Microcystis Computer science Cost-Benefit Analysis Cell lcsh:Medicine 010501 environmental sciences 01 natural sciences Fluorescence Chlorophyceae Cell enumeration medicine Microcystis aeruginosa lcsh:Science 0105 earth and related environmental sciences Multidisciplinary biology Anabaena lcsh:R 010401 analytical chemistry Reproducibility of Results High cell biology.organism_classification Signature (logic) 0104 chemical sciences medicine.anatomical_structure lcsh:Q Biological system |
| Zdroj: | Scientific Reports, Vol 8, Iss 1, Pp 1-12 (2018) |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-018-27406-0 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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