Microzooplankton community structure investigated with imaging flow cytometry and automated live-cell staining

dc.contributor.author Brownlee, Emily F.
dc.contributor.author Olson, Robert J.
dc.contributor.author Sosik, Heidi M.
dc.date.accessioned 2016-08-11T17:03:40Z
dc.date.available 2016-08-11T17:03:40Z
dc.date.issued 2016-05-25
dc.description © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Marine Ecology Progress Series 550 (2016): 65-81, doi:10.3354/meps11687. en_US
dc.description.abstract Protozoa play important roles in grazing and nutrient recycling, but quantifying these roles has been hindered by difficulties in collecting, culturing, and observing these often-delicate cells. During long-term deployments at the Martha’s Vineyard Coastal Observatory (Massachusetts, USA), Imaging FlowCytobot (IFCB) has been shown to be useful for studying live cells in situ without the need to culture or preserve. IFCB records images of cells with chlorophyll fluorescence above a trigger threshold, so to date taxonomically resolved analysis of protozoa has presumably been limited to mixotrophs and herbivores which have eaten recently. To overcome this limitation, we have coupled a broad-application ‘live cell’ fluorescent stain with a modified IFCB so that protozoa which do not contain chlorophyll (such as consumers of unpigmented bacteria and other heterotrophs) can also be recorded. Staining IFCB (IFCB-S) revealed higher abundances of grazers than the original IFCB, as well as some cell types not previously detected. Feeding habits of certain morphotypes could be inferred from their fluorescence properties: grazers with stain fluorescence but without chlorophyll cannot be mixotrophs, but could be either starving or feeding on heterotrophs. Comparisons between cell counts for IFCB-S and manual light microscopy of Lugol’s stained samples showed consistently similar or higher counts from IFCB-S. We show how automated classification through the extraction of image features and application of a machine-learning algorithm can be used to evaluate the large high-resolution data sets collected by IFCBs; the results reveal varying seasonal patterns in abundance among groups of protists. en_US
dc.description.sponsorship This research was supported in part by NSF (grants OCE-1130140, OCE-1434440), NASA (grants NNX11AF07G and NNX13AC98G), the Gordon and Betty Moore Foundation (grants 934 and 2649), and the Woods Hole Oceanographic Institution’s Innovative Technology Program. en_US
dc.identifier.citation Marine Ecology Progress Series 550 (2016): 65-81 en_US
dc.identifier.doi 10.3354/meps11687
dc.identifier.uri https://hdl.handle.net/1912/8232
dc.language.iso en_US en_US
dc.publisher Inter-Research en_US
dc.relation.uri https://doi.org/10.3354/meps11687
dc.rights Attribution 3.0 Unported *
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.subject Protozoa en_US
dc.subject Microzooplankton en_US
dc.subject Automated imaging en_US
dc.subject Fluorescent staining en_US
dc.subject Flow cytometry en_US
dc.title Microzooplankton community structure investigated with imaging flow cytometry and automated live-cell staining en_US
dc.type Article en_US
dspace.entity.type Publication
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relation.isAuthorOfPublication 9754bc81-a0d7-4d4c-be33-a45919842bf7
relation.isAuthorOfPublication 34316a2a-1a85-4e9f-b13e-25d9ecb5131c
relation.isAuthorOfPublication.latestForDiscovery 0bb3330c-fb2a-4e38-9ecb-7e28f595f79d
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