Environmental monitoring involves the quantification of microscopic cells and particles
such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional
microscopy require expert knowledge, are time-intensive and not wellsuited
for automated high throughput. Multispectral imaging flow cytometry (MIFC)
allows measurement of up to 5000 particles per second from a fluid suspension and
can simultaneously capture up to 12 images of every single particle for brightfield
and different spectral ranges, with up to 60x magnification. The high throughput of
MIFC has high potential for increasing the amount and accuracy of environmental
monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food
quality that currently rely on manual microscopic methods. Automated recognition of
particles and cells is also possible, when MIFC is combined with deep-learning computational
techniques. Furthermore, various fluorescence dyes can be used to stain
specific parts of the cell to highlight physiological and chemical features including:
vitality of pollen or algae, allergen content of individual pollen, surface chemical composition
(carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we
outline the great potential for MIFC in environmental research for a variety of
research fields and focal organisms. In addition, we provide best practice
recommendations.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:88517 |
Date | 07 December 2023 |
Creators | Dunker, Susanne, Boyd, Matthew, Durka, Walter, Erler, Silvio, Harpole, W. Stanley, Henning, Silvia, Herzschuh, Ulrike, Hornick, Thomas, Knight, Tiffany, Lips, Stefan, Mäder, Patrick, Motivans Švara, Elena, Mozarowski, Steven, Rakosy, Demetra, Römermann, Christine, Schmitt-Jansen, Mechthild, Stoof-Leichsenring, Kathleen, Stratmann, Frank, Treudler, Regina, Virtanen, Risto, Wendt-Potthoff, Katrin, Wilhelm, Christian |
Publisher | John Wiley & Sons, Inc. |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 10.1002/cyto.a.24658 |
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