Sinking towards destiny: High throughput measurement of phytoplankton sinking rates through time-resolved fluorescence plate spectroscopy

Diatoms are marine primary producers that sink in part due to the density of their silica frustules. Sinking of these phytoplankters is crucial for both the biological pump that sequesters carbon to the deep ocean and for the life strategy of the organism. Sinking rates have been previously measured through settling columns, or with fluorimeters or video microscopy arranged perpendicularly to the direction of sinking. These side-view techniques require large volumes of culture, specialized equipment and are difficult to scale up to multiple simultaneous measures for screening. We established a method for parallel, large scale analysis of multiple phytoplankton sinking rates through top-view monitoring of chlorophyll a fluorescence in microtitre well plates. We verified the method through experimental analysis of known factors that influence sinking rates, including exponential versus stationary growth phase in species of different cell sizes; Thalassiosira pseudonana CCMP1335, chain-forming Skeletonema marinoi RO5A and Coscinodiscus radiatus CCMP312. We fit decay curves to an algebraic transform of the decrease in fluorescence signal as cells sank away from the fluorometer detector, and then used minimal mechanistic assumptions to extract a sinking rate (m d-1) using an RStudio script, SinkWORX. We thereby detected significant differences in sinking rates as larger diatom cells sank faster than smaller cells, and cultures in stationary phase sank faster than those in exponential phase. Our sinking rate estimates accord well with literature values from previously established methods. This well plate-based method can operate as a high throughput integrative phenotypic screen for factors that influence sinking rates including macromolecular allocations, nutrient availability or uptake rates, chain-length or cell size, degree of silification and progression through growth stages. Alternately the approach can be used to phenomically screen libraries of mutants.