I worked remotely as part of the Microbial Biology working group in the department of integrative Marine Ecology of the Stazione Zoologica Anton Dorn (SZN) of Naples, Italy. The SZN was established in 1872 by the German scientist Anton Dohrn. It is a public research organization with the mission to carry out basic biological research, focusing on marine organisms and biodiversity.
The Microbiology group at the SZN mainly focuses on the study of micro-, nano- pico –, bacterio and virioplankton communities. I worked on ultraplankton, planktonic organisms less than 2 micrometers in size (Murphy & Haugen 1985), comprising nano- (2-20μm ) and picoplankton (<2μm) (Sieburth et al. 1978).
My main task was the analysis of Scanning Flow Cytometry data from several research cruises in the Gulf of Naples. Scanning Flow Cytometry is a single-cell counting and analysis method, producing pulse-shape recordings of phytoplankton cells. In-situ and in real-time various optical parameters - such as size, fluorescence and scattering properties are recorded for large numbers of individual cells (Aardema et al. 2018).
This animated video gives a good introduction to Flow Cytometry. Scanning Flow Cytometry works the same way, with the only addition that it performs the optical analyses automated in real time, on board of the research vessel.
The CytoSense used at the SZN has six optical channels to detect Foward & Sideward scatter, Curvature and Red-, Orange and Yellow fluorescence of individual cells in a size range from 0.1 μm up to 4 mm in width.
These are two of the SZN's flow cytometry in-struments at work, at the left in the laboratory at the marine station, on the right real-time ship-board scanning flow cytometry. If you would like to know even more about Flow Cytometry techniques and technologies, this is a very useful resource. Photos: Alexandre Epinoux
The data recorded by the FCM instrument is directly transferred to a computer and can be processed using specialised software. The first step of the data processing is to "gate" the data - this means grouping optically similar cells. The clustering was done manually: The data is displayed in two-dimensional graphs - cytograms - and polygons are drawn around data points forming distinct clusters in the cloud of data points. Each point represents a single cell. The image gallery shows different stages of the clustering and a variety of different cytograms.
In the gating process, I identified 11 distinct cell clusters - 1 group of Synechococcus spp; 4 groups of Cryptophytes, of which 3 in the Nano and 1 in the pico-range; 3 groups of nanoeukaryotes - a generic one, one of potential Coccolithophores (cells with high sideward scatter) and one of potential pennates, i.e. double pulseshapes and high sideward scatter; 1 group of microeukaryotes; and 2 groups of picoeukaryotes, of which one is distinguished by having higher red fluorescence than the other.
Synechococcus spp. are cyanobacteria -i.e. photosynthetic unicellular prokaryotic organism. The generally oval cells can occur solitary or in agglomerationas and chains, the cell content is mostly homogeneous or sometimes with solitary granules (Guiry & Guiry 2020).
Besides chlorophyll a they contain the accessory pigment picoerythrin, due to which they emit orange fluorescence. This allows them to be clearly distinguished in Flow Cytometry analysis. If present, Synechococcus spp. form distinct clusters, with low Forward Scatter and red fluorescence due to their small size, but higher Orange fluorescence than picoeukaryotic cells (Not et al. 2012).
The Cryptophyceae- Cryptophytes - are a class of unicellular protists. Characteristically, they have an asymmetrical cellshape, an invagination and a protein containing, layered structure with periplasts on the surface surrounding the cell and typically two unsymmetrical flagellates. The reduced nucleus is contained within a plastid covered in a four-layered membrane.
The cryptophytes’ light harvesting pigment complex contains different combinations of chlorophyll a and c2, xanthophylls, and phycobiliproteins. Resulting from those pigment combinations, cryptophytes may be coloured brown, red or bluegreenish (Encyclopedia.com 2019, Not et al. 2012 and references within).
In FCM samples, Cryptophytes can be distinguished based on their high Orange to Red fluorescence ratio. They are brighter and have longer light scatters than Synochococcus cells. Different (ataxonomic) clusters of cryptophytes are distinguished based on their optical properties identified through visual analysis of various cytograms.
The term Picoeukaryotes does not form a taxonomic group. Rather it groups the smallest eukaryotic algal cells, cells smaller than 2micrometer in diameter. Generally, they are structurally and morphologically simple, uniform, round photosynthetic cells. They account for a significant part of plankton biomass. Picoeukaryotes can be auto- or mixotrophic and have an important ecological role as primary producers, parasites and predators of bacterial plankton (Massana 2009, Reyes-Prieto 2009).
They have no accessory pigments for orange fluorescence and their red fluorescence, forward and sideward scatter signals are weaker than those of larger eukaryotic cells.
Nano phytoplankton encompasses unicellular (and colonial cells) organisms in a size range between 2 and 20micrometers in diameter. They are more structurally complex than picoplankton organisms. The nanophytoplankton contains a great diversity of morphologies and taxonomic groups, including chlorophytes, diatoms and dinoflagellates. Nano-eukaryotes can be autotrophs, mixotrophs or heterotrophs. Despite picoplankton species having generally higher abundances, Nanophytoplankton often have a larger contribution to the phytoplankton biomass and carbon content (Sherr & Sherr 2009).
In FCM, nanophytoplankton has higher red fluorescence signals than picoeukaryotes and as well larger forward and sideward scatter signals.
Coccolithophores are calcifying planktonic nanoeukaryotes typically 2.0–75.0 μm in cell diameter. They form part of the haptophytes, a clade of photosynthetic algae with two smooth flagella and the so called haptonema, a unique organelle. Characteristic of coccolithophores is their spherical shape and their calceous scales, the coccoliths. They are not the only but the most abundant calciferous phytoplankton group – and, making up about 10% of phytoplankton biomass in the oceans, one of the most numerous of all phytoplankton groups (Tyrell & Young 2009).
In FCM samples, Coccolithophores stand out due to their high Sideward scatter and high polarisation ratios, which are produced by the complex structure of the coccolith surrounding the cells.
Pennates are chain or colonies of multiple unicellular organisms such as diatoms, dinoflagellates etc. They fall into the nanoplankton range regarding fluorescence and forward scattering properties, but can be distinguished based on pulse shapes, containing multiple peaks. Due to the more complex nature of such chains, generally they would produce a larger sideward scatter than single cells. Yet types of singular cells with a complex morphology can have similar optical properties. Thus it cannot be ensured that only actual pennates fall into the pennate-like clusters.
The largest phytoplankton organisms are between 100–200μm long and fall into the microphytoplankton size range, which spans cell sizes from 20-200 μm. Nevertheless, they are less abundant than pico- and nanoplankton. They also encompass a variety of taxa, morphologies and functional types, however, the main representatives of phytoplanktonic microeukaryotes are diatoms as single cells or chains and larger dinoflagellates (Sherr & Sherr 2009).
Microeukaryotes are the group with the highest red fluorescence and largest forward scatter. Instruments such as the Flow Cam technology allow the distinction of different microeukaryote groups through combination of FCM data and high-resolution images. However, since our study focused mostly on picoplankton, this was not feasible for our samples.
Long hours in front of the laptop, gating and analysing data were the main time passing of quarantine & professional practice in Italy.
After gating, the data is exported to csv files which can be further analysed and visualised using statistical software.
Here, we processed the data using the Open Source programme R (R Core Team 2020). DIfferent parameters were calculated for each functional group and visualised in diagrams. Further, GPS and environmental data were combined with the phytoplankton abundance and traits data. Correlations between environmental traits, cell concentrations and cell traits were tested for each functional group.
The results can be explored on the following page.