Imaging flow cytometry for phytoplankton analysis.

This review highlights the concepts and instrumentation of imaging flow cytometry technology and in particular its use for phytoplankton analysis. Imaging flow cytometry, a hybrid technology combining speed and statistical capabilities of flow cytometry with imaging features of microscopy, is rapidly advancing as a cell imaging platform that overcomes many of the limitations of current techniques and contributed significantly to the advancement of phytoplankton analysis in recent years. This review presents the various instrumentation relevant to the field and currently used for assessment of complex phytoplankton communities' composition and abundance, size structure determination, biovolume estimation, detection of harmful algal bloom species, evaluation of viability and metabolic activity and other applications. Also we present our data on viability and metabolic assessment of Aphanizomenon sp. cyanobacteria using Imagestream X Mark II imaging cytometer. Herein, we highlight the immense potential of imaging flow cytometry for microalgal research, but also discuss limitations and future developments.

Using Virtual Filtering Approach to Discriminate Microalgae by Spectral Flow Cytometer.

Fluorescence methods are widely used for the study of marine and freshwater phytoplankton communities. However, the identification of different microalgae populations by the analysis of autofluorescence signals remains a challenge. Addressing the issue, we developed a novel approach using the flexibility of spectral flow cytometry analysis (SFC) and generating a matrix of virtual filters (VF) which allowed thorough examination of autofluorescence spectra. Using this matrix, different spectral emission regions of algae species were analyzed, and five major algal taxa were discriminated. These results were further applied for tracing particular microalgae taxa in the complex mixtures of laboratory and environmental algal populations. An integrated analysis of single algal events combined with unique spectral emission fingerprints and light scattering parameters of microalgae can be used to differentiate major microalgal taxa. We propose a protocol for the quantitative assessment of heterogenous phytoplankton communities at the single-cell level and monitoring of phytoplankton bloom detection using a virtual filtering approach on a spectral flow cytometer (SFC-VF).

Optimizing FlowCam Imaging Flow Cytometry Operation for Classification and Quantification of Microcystis Morphospecies.

Microcystis is a globally known cyanobacterium causing potentially toxic blooms worldwide. Different morphospecies with specific morphological and physiological characters usually co-occur during blooming, and their quantification employing light microscopy can be time-consuming and problematic. A benchtop imaging flow cytometer (IFC) FlowCam (Yokogawa Fluid Imaging Technologies, USA) was used to identify and quantitate different Microcystis morphospecies from environmental samples. We describe here the FlowCam methodology for sample processing and analysis of five European morphospecies of Microcystis common to the temperate zone. The FlowCam technique allows detection of different Microcystis morphospecies providing objective qualitative and quantitative data for statistical analysis.

Changes in Phytoplankton Community Composition and Phytoplankton Cell Size in Response to Nitrogen Availability Depend on Temperature.

The climate-driven changes in temperature, in combination with high inputs of nutrients through anthropogenic activities, significantly affect phytoplankton communities in shallow lakes. This study aimed to assess the effect of nutrients on the community composition, size distribution, and diversity of phytoplankton at three contrasting temperature regimes in phosphorus (P)-enriched mesocosms and with different nitrogen (N) availability imitating eutrophic environments. We applied imaging flow cytometry (IFC) to evaluate complex phytoplankton communities changes, particularly size of planktonic cells, biomass, and phytoplankton composition. We found that N enrichment led to the shift in the dominance from the bloom-forming cyanobacteria to the mixed-type blooming by cyanobacteria and green algae. Moreover, the N enrichment stimulated phytoplankton size increase in the high-temperature regime and led to phytoplankton size decrease in lower temperatures. A combination of high temperature and N enrichment resulted in the lowest phytoplankton diversity. Together these findings demonstrate that the net effect of N and P pollution on phytoplankton communities depends on the temperature conditions. These implications are important for forecasting future climate change impacts on the world's shallow lake ecosystems.

Comparative analysis of freshwater phytoplankton communities in two lakes of Burabay National Park using morphological and molecular approaches.

We analyzed phytoplankton assemblages' variations in oligo-mesotrophic Shchuchie and Burabay lakes using traditional morphological and next-generation sequencing (NGS) approaches. The total phytoplankton biodiversity and abundance estimated by both microscopy and NGS were significantly higher in Lake Burabay than in Lake Shchuchie. NGS of 16S and 18S rRNA amplicons adequately identify phytoplankton taxa only on the genera level, while species composition obtained by microscopic examination was significantly larger. The limitations of NGS analysis could be related to insufficient coverage of freshwater lakes phytoplankton by existing databases, short algal sequences available from current instrumentation, and high homology of chloroplast genes in eukaryotic cells. However, utilization of NGS, together with microscopy allowed us to perform a complete taxonomic characterization of phytoplankton lake communities including picocyanobacteria, often overlooked by traditional microscopy. We demonstrate the high potential of an integrated morphological and molecular approach in understanding the processes of organization in aquatic ecosystem assemblages.

Semi-automated classification of colonial Microcystis by FlowCAM imaging flow cytometry in mesocosm experiment reveals high heterogeneity during seasonal bloom.

A machine learning approach was employed to detect and quantify Microcystis colonial morphospecies using FlowCAM-based imaging flow cytometry. The system was trained and tested using samples from a long-term mesocosm experiment (LMWE, Central Jutland, Denmark). The statistical validation of the classification approaches was performed using Hellinger distances, Bray-Curtis dissimilarity, and Kullback-Leibler divergence. The semi-automatic classification based on well-balanced training sets from Microcystis seasonal bloom provided a high level of intergeneric accuracy (96-100%) but relatively low intrageneric accuracy (67-78%). Our results provide a proof-of-concept of how machine learning approaches can be applied to analyze the colonial microalgae. This approach allowed to evaluate Microcystis seasonal bloom in individual mesocosms with high level of temporal and spatial resolution. The observation that some Microcystis morphotypes completely disappeared and re-appeared along the mesocosm experiment timeline supports the hypothesis of the main transition pathways of colonial Microcystis morphoforms. We demonstrated that significant changes in the training sets with colonial images required for accurate classification of Microcystis spp. from time points differed by only two weeks due to Microcystis high phenotypic heterogeneity during the bloom. We conclude that automatic methods not only allow a performance level of human taxonomist, and thus be a valuable time-saving tool in the routine-like identification of colonial phytoplankton taxa, but also can be applied to increase temporal and spatial resolution of the study.

Spectral and Imaging Flow Cytometry in Phytoplankton Research.

Spectral and imaging flow cytometry are emerging technologies that allow quantifying spectral, fluorescent, and/or morphological parameters of heterogeneous cellular populations. The protocol describes a detailed step-by-step analysis of microalgae using these techniques and examples from our laboratory (Aphanizomenon sp., Cryptomonas pyrenoidifera, and Chlorella sp.). Moreover, the chapter will be helpful to scientists who want to perform spectral flow cytometry and apply principal component analysis.