Endometabolic profiling of pigmented glacier ice algae: the impact of sample processing.

INTRODUCTION: Glacier ice algae, mainly Ancylonema alaskanum and Ancylonema nordenskiöldi, bloom on Greenland Ice Sheet bare ice surfaces. They significantly decrease surface albedo due to their purple-brown pigmentation, thus increasing melt. Little is known about their metabolic adaptation and factors controlling algal growth dynamics and pigment formation. A challenge in obtaining such data is the necessity of melting samples, which delays preservation and introduces bias to metabolomic analysis. There is a need to evaluate the physiological response of algae to melting and establish consistent sample processing strategies for metabolomics of ice microbial communities. OBJECTIVES: To address the impact of sample melting procedure on metabolic characterization and establish a processing and analytical workflow for endometabolic profiling of glacier ice algae. METHODS: We employed untargeted, high-resolution mass spectrometry and tested the effect of sample melt temperature (10, 15, 20 °C) and processing delay (up to 49 h) on the metabolome and lipidome, and complemented this approach with cell counts (FlowCam), photophysiological analysis (PAM) and diversity characterization. RESULTS AND CONCLUSION: We putatively identified 804 metabolites, with glycerolipids, glycerophospholipids and fatty acyls being the most prominent superclasses (> 50% of identified metabolites). Among the polar metabolome, carbohydrates and amino acid-derivatives were the most abundant. We show that 8% of the metabolome is affected by melt duration, with a pronounced decrease in betaine membrane lipids and pigment precursors, and an increase in phospholipids. Controlled fast melting at 10 °C resulted in the highest consistency, and is our recommendation for future supraglacial metabolomics studies.

Functional ecology of planktonic ciliates: Measuring mortality rates in response to starvation.

Population dynamics of aquatic ciliates are controlled "bottom-up" via food supply and "top-down" by grazing and parasitism. While intrinsic growth rates of ciliates under saturating food conditions have been studied in some detail, mortality rates induced by starvation have received little attention thus far. To this end, we examined the response of three algivorous freshwater ciliate species to starvation using three different optical methods. Two of these methods, i.e. ciliate mortality rates (δ) estimated from (i) numerical response experiments and (ii) the rate of decline (ROD) in cell numbers, investigated the response of the ciliate population using conventional light microscopy. The third method, imaging cytometry using a FlowCAM instrument, monitored single cells during the starvation experiment. Like light microscopy, the FlowCAM approach estimated δ based on ROD in the experimental containers. However, imaging cytometry also measured the relative cellular chlorophyll a content in the ciliates' food vacuoles as a proxy for the nutritional status of the cells. The linear decline of the cellular chl. a yielded an independent estimate of δ that was similar to δ calculated from ROD. Additionally, the FlowCAM measurements revealed a high degree of phenotypic plasticity of the ciliates when exposed to starvation.

Microplastics' Shape and Morphology Analysis in the Presence of Natural Organic Matter Using Flow Imaging Microscopy.

Ubiquitous microplastics in urban waters have raised substantial public concern due to their high chemical persistence, accumulative effects, and potential adverse effects on human health. Reliable and standardized methods are urgently needed for the identification and quantification of these emerging environmental pollutants in wastewater treatment plants (WWTPs). In this study, we introduce an innovative rapid approach that employs flow imaging microscopy (FlowCam) to simultaneously identify and quantify microplastics by capturing high-resolution digital images. Real-time image acquisition is followed by semi-automated classification using customized libraries for distinct polyethylene (PE) and polystyrene (PS) microplastics. Subsequently, these images are subjected to further analysis to extract precise morphological details of microplastics, providing insights into their behavior during transport and retention within WWTPs. Of particular significance, a systematic investigation was conducted to explore how the presence of natural organic matter (NOM) in WWTPs affects the accuracy of the FlowCam's measurement outputs for microplastics. It was observed that varying concentrations of NOM induced a more curled shape in microplastics, indicating the necessity of employing pre-treatment procedures to ensure accurate microplastic identification when utilizing the FlowCam. These observations offer valuable new perspectives and potential solutions for designing appropriate treatment technologies for removing microplastics within WWTPs.

Label-Free, Flow-Imaging Methods for Determination of Cell Concentration and Viability.

PURPOSE: To investigate the potential of two flow imaging microscopy (FIM) techniques (Micro-Flow Imaging (MFI) and FlowCAM) to determine total cell concentration and cell viability. METHODS: B-lineage acute lymphoblastic leukemia (B-ALL) cells of 2 different donors were exposed to ambient conditions. Samples were taken at different days and measured with MFI, FlowCAM, hemocytometry and automated cell counting. Dead and live cells from a fresh B-ALL cell suspension were fractionated by flow cytometry in order to derive software filters based on morphological parameters of separate cell populations with MFI and FlowCAM. The filter sets were used to assess cell viability in the measured samples. RESULTS: All techniques gave fairly similar cell concentration values over the whole incubation period. MFI showed to be superior with respect to precision, whereas FlowCAM provided particle images with a higher resolution. Moreover, both FIM methods were able to provide similar results for cell viability as the conventional methods (hemocytometry and automated cell counting). CONCLUSION: FIM-based methods may be advantageous over conventional cell methods for determining total cell concentration and cell viability, as FIM measures much larger sample volumes, does not require labeling, is less laborious and provides images of individual cells.

In Vivo Single-Cell Fluorescence and Size Scaling of Phytoplankton Chlorophyll Content.

In unicellular phytoplankton, the size scaling exponent of chlorophyll content per cell decreases with increasing light limitation. Empirical studies have explored this allometry by combining data from several species, using average values of pigment content and cell size for each species. The resulting allometry thus includes phylogenetic and size scaling effects. The possibility of measuring single-cell fluorescence with imaging-in-flow cytometry devices allows the study of the size scaling of chlorophyll content at both the inter- and intraspecific levels. In this work, the changing allometry of chlorophyll content was estimated for the first time for single phytoplankton populations by using data from a series of incubations with monocultures exposed to different light levels. Interspecifically, our experiments confirm previous modeling and experimental results of increasing size scaling exponents with increasing irradiance. A similar pattern was observed intraspecifically but with a larger variability in size scaling exponents. Our results show that size-based processes and geometrical approaches explain variations in chlorophyll content. We also show that the single-cell fluorescence measurements provided by imaging-in-flow devices can be applied to field samples to understand the changes in the size dependence of chlorophyll content in response to environmental variables affecting primary production.IMPORTANCE The chlorophyll concentrations in phytoplankton register physiological adjustments in cellular pigmentation arising mainly from changes in light conditions. The extent of these adjustments is constrained by the size of the phytoplankton cells, even within single populations. Hence, variations in community chlorophyll derived from photoacclimation are also dependent on the phytoplankton size distribution.

Determination of the Porosity of PLGA Microparticles by Tracking Their Sedimentation Velocity Using a Flow Imaging Microscope (FlowCAM).

PURPOSE: To investigate whether particle sedimentation velocity tracking using a flow imaging microscope (FlowCAM) can be used to determine microparticle porosity. METHODS: Two different methods were explored. In the first method the sedimentation rate of microparticles was tracked in suspending media with different densities. The porosity was calculated from the average apparent density of the particles derived by inter- or extrapolation to the density of a suspending medium in which the sedimentation velocity was zero. In the second method, the microparticle size and sedimentation velocity in one suspending fluid were used to calculate the density and porosity of individual particles by using the Stokes' law of sedimentation. RESULTS: Polystyrene beads of different sizes were used for the development, optimization and validation of the methods. For both methods we found porosity values that were in excellent agreement with the expected values. Both methods were applied to determine the porosity of three PLGA microparticle batches with different porosities (between about 4 and 52%). With both methods we obtained microparticle porosity values similar to those obtained by mercury intrusion porosimetry. CONCLUSIONS: We developed two methods to determine average microparticle density and porosity by sedimentation velocity tracking, using only a few milligrams of powder.

Monitoring cell-specific neutral lipid accumulation in Phaeodactylum tricornutum (Bacillariophyceae) with Nile Red staining - a new method for FlowCAM.

With the fluorescent stain Nile Red (NR), phytoplankton lipid accumulation can be monitored quickly and in situ. In the light of recent results in phytoplankton diversity research, there is also a need for cell- and species-specific lipid measurement techniques. The objective of this work was to investigate whether cell-specific phytoplankton lipid accumulation could be monitored with the image-based particle analyzer FlowCAM™ and NR staining. Applying Phaeodactylum tricornutum as a model species, we compared the FlowCAM method to two established lipid quantification methods: spectrofluorometric NR fluorescence measurement and total lipid analysis by gas chromatography. The experiment was carried out in batch cultures under nitrogen limitation to induce lipid accumulation. We showed significant correlation between the three different lipid quantification methods confirming the applicability of the novel FlowCAM method in cell-specific and near real-time lipid quantification. Furthermore, with the method described here, the lipid content of taxonomically distinguished cells can eventually be measured from multispecies cultures, opening several new possibilities to study species-specific responses to stress conditions and the complementarity effect.

Life cycle size dynamics in Didymosphenia geminata (Bacillariophyceae).

Didymosphenia geminata has received a great deal of attention in the last 25 years, and considerable effort has gone into determining the origin, ecological impact, and economic consequences of its invasive behavior. While environmental conditions are a controlling influence in distribution, the extreme success of the species may be tied to its basic biology and life history. Little is known, however, about population dynamics, size restoration and reproduction of D. geminata. The objective of this study was to determine the temporal patterns in cell size frequency, size restoration strategy, and synchronization of life cycles between populations in close proximity. We implemented FlowCam technology to measure the length of more than 100,000 D. geminata cells from two sites in South Boulder Creek, Colorado over 1 year. We applied finite mixture modeling to uncover temporal patterns in size distribution. Our results show that collections of D. geminata exhibited a complex, multimodal size distribution, almost always containing four overlapping age cohorts. We failed to observe direct visual evidence of the sexual phase. Multiple abrupt and directional shifts in size distribution, however, were documented providing conclusive evidence of cell size restoration. Lastly, nodules in close proximity were asynchronous with respect to size frequency profiles and size diminution, highlighting the relevance of spatial heterogeneity in in situ diatom size dynamics. This study is the first to document the complexity of diatom cell size distribution in a lotic system, size restoration in D. geminata, and the variability in rates of size reduction at microhabitat spatial scales.

Digital imaging-in-flow (FlowCAM) and probabilistic machine learning to assess the sonolytic disinfection of cyanobacteria in sewage wastewater.

Assessing the cyanobacteria disinfection in sewage and its compliance with international-standards requires determining the concentration and viability, which can be achieve using Imaging Flow Cytometry device called FlowCAM. The objective is to thoroughly investigate the sonolytic morphological changes and disinfection-performance towards toxic cyanobacteria existing in sewage using the FlowCAM. After optimizing the process conditions, over 80% decline in cyanobacterial cell counts was observed, accompanied by an additional 10-15% of cells exhibiting injuries, as confirmed through morphological investigation. Moreover, for the first time, the experimentally collected data was utilized to build deep-learning probabilistic-neural-networks (PNN) and natural-gradient-boosting (NGBoost) models for predicting disinfection efficiency and ABD area as target outputs. The findings suggest that the NGBoost model exhibited superior prediction performance for both targets, with high test coefficient of determination (R2 > 0.87) and lower test errors (RMSE < 7.10, MAE < 4.14). The confidence interval examination in NGBoost prediction performance showed a minute variation from the experimentally calculated values, suggesting a high accuracy in model prediction. Finally, SHAP analysis suggests the sonolytic time alone contributes around 50% to the cyanobacteria disinfection. Overall, the findings demonstrate the effectiveness of the FlowCAM device and the potential of machine-learning modeling in predicting disinfection outcomes.

Temperature-dependent resistance to starvation of three contrasting freshwater ciliates.

We investigated the temperature-dependent response to starvation of three contrasting freshwater ciliates (Ciliophora). The cyst-forming algivorous species Meseres corlissi and the bactivorous species Glaucomides bromelicola, which cannot form cysts, co-occur in the reservoirs (tanks) of tree bromeliads. The mixotrophic species Coleps spetai is common in many lakes. We hypothesized that the ciliates' different traits and life strategies would affect their survival rates and temperature sensitivity under food depleted conditions. We measured the decline of the ciliate populations in microcosm experiments at different temperatures for several days. We used an imaging flow cytometer to size the ciliates and documented their morphological and physiological changes in response to starvation. We found that the cyst-forming species had the highest mortality rates but may endure long-term starvation by encystment. The sympatric, non-encysting species suffered the lowest mortality rates and could survive for more than three weeks without food. The mixotrophic species had intermediate mortality rates but showed the highest phenotypic plasticity in response to starvation. A significant fraction of the C. spetai population appeared unaffected by starvation, suggesting that the endosymbionts provided some resources to the host cells. The mean mortality rate per day of all three species increased with temperature by 0.09 °C-1.

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.

An artificial intelligence approach for identification of microalgae cultures.

In this work, a model for the characterization of microalgae cultures based on artificial neural networks has been developed. The characterization of microalgae cultures is essential to guarantee the quality of the biomass, and the objective of this work is to achieve a simple and fast method to address this issue. Data acquisition was performed using FlowCam, a device capable of capturing images of the cells detected in a culture sample, which are used as inputs by the model. The model can distinguish between 6 different genera of microalgae, having been trained with several species of each genus. It was further complemented with a classification threshold to discard unwanted objects while improving the overall accuracy of the model. The model achieved an accuracy of up to 97.27% when classifying a culture. The results demonstrate the effectiveness of the Deep Learning models for the characterization of microalgae cultures, it being a useful tool for the monitoring of microalgae cultures in large-scale production facilities while providing accurate characterization over a wide range of genera.

A comparison between the FlowCam 8100, microscopy, and sandwich hybridization assay for quantifying abundances of the saxitoxin-producing dinoflagellate, Alexandrium catenella.

Light microscopy, FlowCam, and sandwich hybridization assay (SHA) are three approaches that facilitate the monitoring of harmful algal bloom (HAB) forming phytoplankton. Yet, cross-comparisons among these techniques have not been conducted. This study addressed that gap using the saxitoxin-producing 'red tide' dinoflagellate Alexandrium catenella, a species responsible for blooms and paralytic shellfish poisoning worldwide. To achieve this goal, the dynamic ranges of each technique were compared using A. catenella cultures spanning low (pre-bloom), moderate (bloom), and high (dense bloom) levels. To assess field detection, water samples containing very low (<3 cells mL-1) A. catenella levels were collected from Long Island Sound, USA (Jun-Aug 2021) and evaluated using each method. Field samples were also spiked with A. catenella to high (160 cells mL-1) or low (40 cells mL-1) concentrations. In general, microscopy, FlowCam, and SHA returned comparable A. catenella cell concentrations for all tests. Mean cell concentrations from laboratory intercalibration experiments were not significantly different for any method or concentration (ANOVA, p > 0.05). However, relative to microscopy at times SHA produced non-detect signals <2 cells mL-1 in field samples and the FlowCam slightly underestimated cell concentrations when A. catenella abundances were high in laboratory and field samples. Mean cell concentrations of spike experiments were not significantly different for any test date, sampling location, or method, despite variability among methods within the high concentration treatment (ANOVA, p > 0.05 for all treatments). Findings are relevant to HAB researchers, managers, and public health officials because they help reconcile disparate cell abundance datasets that inform numerical models and enhance HAB monitoring and prediction. Results are also likely broadly applicable to several HAB species.

FlowCam 8400 and FlowCam Cyano Phytoplankton Classification and Viability Staining by Imaging Flow Cytometry.

This chapter provides a protocol for a detailed evaluation of phytoplankton and nuisance cyanobacteria with the FlowCam 8400 and the FlowCam Cyano. The chapter includes (i) detailed description of the quality control of fluorescent mode of the FlowCam, (ii) detailing methods for discriminating nuisance cyanobacteria using the FlowCam Cyano, how to set up libraries and classification routines for commonly used classification reports, and (iii) detailing methods for viability staining to quantify LIVE versus DEAD phytoplankton using the FlowCam 8400.

Phytoplankton and particle size spectra indicate intense mixotrophic dinoflagellates grazing from summer to winter.

Mixotrophic dinoflagellates (MTD) are a diverse group of organisms often responsible for the formation of harmful algal blooms. However, the development of dinoflagellate blooms and their effects on the plankton community are still not well explored. Here we relate the species succession of MTD with parallel changes of phytoplankton size spectra during periods of MTD dominance. We used FlowCAM analysis to acquire size spectra in the range 2-200 µm every one or two weeks from July to December 2007 at Helgoland Roads (Southern North Sea). Most size spectra of dinoflagellates were bimodal, whereas for other groups, e.g. diatoms and autotrophic flagellates, the spectra were unimodal, which indicates different resource use strategies of autotrophs and mixotrophs. The biomass lost in the size spectrum correlates with the potential grazing pressure of MTD. Based on size-based analysis of trophic linkages, we suggest that mixotrophy, including detritivory, drives species succession and facilitates the formation of bimodal size spectra. Bimodality in particular indicates niche differentiation through grazing of large MTD on smaller MTD. Phagotrophy of larger MTD may exceed one of the smaller MTD since larger prey was more abundant than smaller prey. Under strong light limitation, a usually overlooked refuge strategy may derive from detritivory. The critical role of trophic links of MTD as a central component of the plankton community may guide future observational and theoretical research.

Oil-Immersion Flow Imaging Microscopy for Quantification and Morphological Characterization of Submicron Particles in Biopharmaceuticals.

Flow imaging microscopy (FIM) is widely used to analyze subvisible particles starting from 2 µm in biopharmaceuticals. Recently, an oil-immersion FIM system emerged, the FlowCam Nano, designed to enable the characterization of particle sizes even below 2 µm. The aim of our study was to evaluate oil-immersion FIM (by using FlowCam Nano) in comparison to microfluidic resistive pulse sensing and resonant mass measurement for sizing and counting of particles in the submicron range. Polystyrene beads, a heat-stressed monoclonal antibody formulation and a silicone oil emulsion, were measured to assess the performance on biopharmaceutical relevant samples, as well as the ability to distinguish particle types based on instrument-derived morphological parameters. The determination of particle sizes and morphologies suffers from inaccuracies due to a low image contrast of small particles and light-scattering effects. The ill-defined measured volume impairs an accurate concentration determination. Nevertheless, FlowCam Nano in its current design complements the limited toolbox of submicron particle analysis of biopharmaceuticals by providing particle images in a size range that was previously not accessible with commercial FIM instruments.

LifeWatch observatory data: phytoplankton observations in the Belgian Part of the North Sea.

BACKGROUND: This paper describes a phytoplankton data series generated through systematic observations in the Belgian Part of the North Sea (BPNS). Phytoplankton samples were collected during multidisciplinary sampling campaigns, visiting nine nearshore stations with monthly frequency and an additional eight offshore stations on a seasonal basis. NEW INFORMATION: The data series contain taxon-specific phytoplankton densities determined by analysis with the Flow Cytometer And Microscope (FlowCAM®) and associated image-based classification. The classification is performed by two separate semi-automated classification systems, followed by manual validation by taxonomic experts. To date, 637,819 biological particles have been collected and identified, yielding a large dataset of validated phytoplankton images. The collection and processing of the 2017-2018 dataset are described, along with its data curation, quality control and data storage. In addition, the classification of images using image classification algorithms, based on convolutional neural networks (CNN) from 2019 onwards, is also described. Data are published in a standardised format together with environmental parameters, accompanied by extensive metadata descriptions and finally labelled with digital identifiers for traceability. The data are published under a CC-BY 4.0 licence, allowing the use of the data under the condition of providing the reference to the source.

Species interactions mediate thermal evolution.

Understanding whether populations and communities can evolve fast enough to keep up with ongoing climate change is one of the most pressing issues in biology today. A growing number of studies have documented rapid evolutionary responses to warming, suggesting that populations may be able to persist despite temperature increases. The challenge now is to better understand how species interactions, which are ubiquitous in nature, mediate these population responses to warming. Here, we use laboratory natural selection experiments in a freshwater community to test hypotheses related to how thermal evolution of Daphnia pulex to two selection temperatures (12 and 18°C) is mediated by rapid thermal evolution of its algal resource (Scenedesmus obliquus) or by the presence of the zooplankton predator Chaoborus americanus. We found that cold-evolved algae (a high-quality resource) facilitated the evolution of increased thermal plasticity in Daphnia populations selected at 12°C, for both body size and per capita growth rates (r). Conversely, warm-evolved algae facilitated the evolution of increased r thermal plasticity for Daphnia selected at 18°C. Lastly, we found that the effect of selection temperature on evolved Daphnia body size was more pronounced when Daphnia were also reared with predators. These data demonstrate that trait evolution of a focal population to the thermal environment can be affected by both bottom-up and top-down species interactions and that rapid temperature evolution of a resource can have cascading effects on consumer thermal evolution. Our study highlights the importance of incorporating species interactions when estimating ecological and evolutionary responses of populations and communities to ongoing temperature warming.

A new method for acquiring images of meiobenthic images using the FlowCAM.

The purpose of this study was to develop a new method for investigating sediment-inhabiting meiobenthos using the Flow Cytometer And Microscope (FlowCAM). Meiobenthos are widely recognized as a useful indicator for assessing the effects of anthropogenic and natural disturbances in both shallow and deep ocean ecosystems. These small benthic invertebrates are traditionally investigated by individually counting and identifying specimens under a microscope, which is labor intensive and time consuming. However, FlowCAM, which was originally developed to semiautomatically analyze microplankton, has the potential to resolve these challenges. Meiobenthic specimens were extracted from sediment using the centrifugal separation method and were then pipetted into the FlowCAM system and imaged. The images were then used to classify and count the specimens at high taxonomic levels to verify the effectiveness of this method compared with traditional methods. We found that FlowCAM system: •Enabled sufficient meiobenthic images to be obtained to allow the identification and classification of specimens at high taxonomic levels.•Obtained comparable numbers of individuals to traditional methods.•Has the potential to rapidly process large the volumes of meiobenthos samples that are required when monitoring seasonal and spatial variation in ocean ecosystems and conducting long-term environmental impact assessments.

Assessment of imaging-in-flow system (FlowCAM) for systematic ballast water management.

Assessing the disinfection of ballast water and its compliance with international standards requires determining the size, viability, and concentration of planktonic organisms. The FlowCAM (Flow Cytometer and Microscope) is an Imaging Flow Cytometry designed to obtain the particle concentration, images, and quantitative morphologic information. The objective in this paper is to establish the basis for transforming the FlowCAM from being a laboratory analyzer into a tool for systematic monitoring of ballast water. The capacity of the FlowCAM was evaluated by analyzing artificial microbeads, phytoplankton monocultures, and real seawater samples. Microbead analyses reported high accuracy and precision in size and concentration measurements. Monoculture analyses showed the effect of disinfection treatments in cell appearance and growth. Low concentration and heterogeneity of particles in real seawater analyses require the comprehensive observation of images by experts. Additionally, some physical characteristics of the device must be improved. The optimization of device configuration enables the quick transferring of files and information between parties involved in ballast water management. FlowCAM may become a feasible technology for this after the device and protocols are adapted.