Where Do All the Phytoplankton Go? Challenges in Keeping Track of Viable Cells in Phytoplankton Communities Using Flow Cytometry and Cell Staining
Where Do All the Phytoplankton Go? Challenges in Keeping Track of Viable Cells in Phytoplankton Communities Using Flow Cytometry and Cell Staining
Abstract:
Understanding the dynamics of phytoplankton communities has traditionally focused on differences in growth and related processes among taxa. It is now appreciated that differences in mortality could be equally important in contributing to these dynamics. Studying mortality in communities is difficult, especially on relevant time scales, which could be as short as hours to days. Flow cytometry can potentially provide solutions, because it can allow discrimination of different taxa, and when combined with staining, distinguish live and dead cells. We applied flow cytometry and staining to phytoplankton communities in a model system: a small, well-studied, urban pond in southeastern Wisconsin. Using flow cytometry, it was possible to resolve up to six dominant taxa (most <37 µm) and track them through an annual cycle. However, the axes traditionally used, forward scatter (FSC, related to cell size) and red fluorescence (FL3, related to chlorophyll a content) offered poor discrimination. Addition of orange fluorescence (FL2, traditionally related to phycobilipigments) and side scatter (SSC, related to cell surface characteristics) improved separation of taxa, but reproducibility (i.e. the specific position of the taxa on axes) was also more sensitive to environmental variation in the case of the fluorescence parameters. Dead cells could be distinguished by green fluorescence (FL1, using SYTOX Green©), but the stain also affected other fluorescence channels, requiring compensation. Correlations of numbers of dead cells with environmental factors (e.g. temperature, nutrient concentrations, irradiance) were generally poor, suggesting the greater importance of biotic versus abiotic variables in community mortality dynamics. Ongoing work is focusing on the effects of viral pathogens, grazing and allelopathic interactions using experimental manipulations and individual-based modeling.