Phytoplankton and their Analysis by Flow Cytometry

Abstract

OverviewThis chapter outlines how flow cytometry can be used for the analysis of phytoplankton: from basic and straightforward analysis to more challenging applications. Whereas most applications of flow cytometry in aquatic science are still laboratory-based, the emphasis of this chapter is on its potential to be used in situ, operated on a high frequency basis. This permits high-resolution sampling in time and space, which is crucial for our understanding of aquatic microbial ecosystems. Beginning with a basic description of the target particles, a sketch is made of the aquatic environment of these microorganisms and specific properties of the environment that may be very different from typical biomedical or plant research conditions. Some phytoplankton-related limitations and pitfalls are discussed as well as special instruments and instrument modification for phytoplankton analysis. Phytoplankton sampling is described with consideration to ''critical scales'', including the use of platforms such as research ships and ships of opportunity, submerged use in vertical casts or on autonomous underwater vehicles and moored platforms. Various applications are presented, including the screening of species, probing phytoplankton biodiversity, monitoring ''harmful algal blooms'', studying population-related processes, and cell-related processes and functioning. Plankton abundance patterns in the sea are assessed and the coupling of flow cytometry data to ocean optics and physics is advocated. Finally, the potential use of flow cytometry in protection and warning is discussed, including the monitoring of harmful algal blooms, water quality in the aquaculture industry, bathing waters and the drinking water industry, as well as with bio-indicatiors and the control of ship's ballast water treatment systems.

PlanktoVision - an automated analysis system for the identification of phytoplankton

“…The classification results are summarized as followed: ADIAC (37 taxa, 75–90% recognition), which is a system for the automated analysis of diatom slides [19]; Zooscan (29 groups, 75–85% recognition), which is a platform for the analysis of mesozooplankton where samples are imaged with a water-proof scanner [20,21]; SIPPER (5 groups, recognition of 75–90%) [22] and VPR (7 groups, 72% recognition) [23], which both are system for the analysis of mesozooplankton, where the organisms are imaged during the sampling; DiCANN (3–23 species, 70–87% recognition), which is a system for the classification of dinoflagellates [24]; Cytosense (30 groups, 91% recognition), which is a flow cytometric approach [25]. …”

Functional analysis and classification of phytoplankton based on data from an automated flow cytometer

“…Analysis of aquatic microorganisms performed by flow cytometry is currently used to address their abundance, diversity, and dynamics (10). Data analysis for conventional flow cytometers is based on a set of real values (peak, area, pulse width) corresponding to the light scatter and fluorescence signals recorded for each single particle as it is intercepted by the light source.…”

“…can now be observed (8). Phytoplankton communities are also morphologically diverse, varying in shape and size, as a result of adaptation to physical processes (such as hydrodynamics, irradiance), grazing (formation of colonies, extracellular spikes), nutrient uptake (variation of the volume/surface ratio) (9–13).…”

“…Although being an ataxonomical method, FCM allows the discrimination of particle clusters within an aquatic sample based on their optical fingerprints (fluorescence signatures and scattering properties). In the last 20 years, flow cytometers have been designed to marine applications (10). This is the case for the CytoSense instrument (Cytobuoy B.V.).…”

Recommendations on methods for the detection and control of biological pollution in marine coastal waters

“…the deployment of fouling panels at -entry‖ points or -hot spots‖ where settling NIS may be expected. Special attention should be paid to the development and application of modern cytometric approaches, such as molecular barcoding and individual particle analysis and imaging devices (Paul et al 2007, Dubelaar et al 2007), especially for the early detection of new introductions. Automated systems (e.g.…”