A microfluidic microalgae detection system for cellular physiological response based on an object detection algorithm.

The composition of species and the physiological status of microalgal cells serve as significant indicators for monitoring marine environments. Symbiotic with corals, Symbiodiniaceae are more sensitive to the environmental response. However, current methods for evaluating microalgae tend to be population-based indicators that cannot be focused on single-cell level, ignoring potentially heterogeneous cells as well as cell state transitions. In this study, we proposed a microalgal cell detection method based on computer vision and microfluidics, which combined microscopic image processing, microfluidic chip and convolutional neural network to achieve label-free, sheathless, automated and high-throughput microalgae identification and cell state assessment. By optimizing the data import, training process and model architecture, we solved the problem of identifying tiny objects at the micron scale, and the optimized model was able to perform the tasks of cell multi-classification and physiological state assessment with more than 95% mean average precision. We discovered a novel transition state and explored the thermal sensitivity of three clades of Symbiodiniaceae, and discovered the phenomenon of cellular heat shock at high temperatures. The evolution of the physiological state of Symbiodiniaceae cells is very important for directional cell evolution and early warning of coral ecosystem health.

Macroalgal deep genomics illuminate multiple paths to aquatic, photosynthetic multicellularity.

Macroalgae are multicellular, aquatic autotrophs that play vital roles in global climate maintenance and have diverse applications in biotechnology and eco-engineering, which are directly linked to their multicellularity phenotypes. However, their genomic diversity and the evolutionary mechanisms underlying multicellularity in these organisms remain uncharacterized. In this study, we sequenced 110 macroalgal genomes from diverse climates and phyla, and identified key genomic features that distinguish them from their microalgal relatives. Genes for cell adhesion, extracellular matrix formation, cell polarity, transport, and cell differentiation distinguish macroalgae from microalgae across all three major phyla, constituting conserved and unique gene sets supporting multicellular processes. Adhesome genes show phylum- and climate-specific expansions that may facilitate niche adaptation. Collectively, our study reveals genetic determinants of convergent and divergent evolutionary trajectories that have shaped morphological diversity in macroalgae and provides genome-wide frameworks to understand photosynthetic multicellular evolution in aquatic environments.

State 1 and State 2 in Photosynthetic Apparatus of Red Microalgae and Cyanobacteria.

Imbalanced light absorption by photosystem I (PSI) and photosystem II (PSII) in oxygenic phototrophs leads to changes in interaction of photosystems altering the linear electron flow. In plants and green algae, this imbalance is mitigated by a partial migration of the chlorophyll a/b containing light-harvesting antenna between the two photosystem core complexes. This migration is registered as fluorescence changes of the pigment apparatus and is termed the reverse transitions between States 1 and 2. By contrast, the molecular mechanism of State 1/2 transitions in phycobilisome (PBS)-containing photosynthetics, cyanobacteria and red algae, is still insufficiently understood. The suggested hypotheses - PBS movement along the surface of thylakoid membrane between PSI and PSII complexes, reversible PBS detachment from the dimeric PSII complex, and spillover - have some limitations as they do not fully explain the accumulated data. Here, we have recorded changes in the stationary fluorescence emission spectra of red algae and cyanobacteria in States 1/2 at room temperature, which allowed us to offer an explanation of the existing contradictions. The change of room temperature fluorescence of chlorophyll belonged to PSII was revealed, while the fluorescence of PBS associated with the PSII complexes remained during States 1/2 transitions at the stable level. Only the reversible dissociation of PBS from the monomeric PSI was revealed earlier which implied different degree of surface contact of PBS with the two photosystems. The detachment of PBS from the PSI corresponds to ferredoxin oxidation as electron carrier and the increase of cyclic electron transport in the pigment apparatus in State I.

Identification and Quantification of Glycans in Whole Cells: Architecture of Microalgal Polysaccharides Described by Solid-State Nuclear Magnetic Resonance.

Microalgae are photosynthetic organisms widely distributed in nature and serve as a sustainable source of bioproducts. Their carbohydrate components are also promising candidates for bioenergy production and bioremediation, but the structural characterization of these heterogeneous polymers in cells remains a formidable problem. Here we present a widely applicable protocol for identifying and quantifying the glycan content using magic-angle-spinning (MAS) solid-state NMR (ssNMR) spectroscopy, with validation from glycosyl linkage and composition analysis deduced from mass-spectrometry (MS). Two-dimensional 13C-13C correlation ssNMR spectra of a uniformly 13C-labeled green microalga Parachlorella beijerinckii reveal that starch is the most abundant polysaccharide in a naturally cellulose-deficient strain, and this polymer adopts a well-organized and highly rigid structure in the cell. Some xyloses are present in both the mobile and rigid domains of the cell wall, with their chemical shifts partially aligned with the flat-ribbon 2-fold xylan identified in plants. Surprisingly, most other carbohydrates are largely mobile, regardless of their distribution in glycolipids or cell walls. These structural insights correlate with the high digestibility of this cellulose-deficient strain, and the in-cell ssNMR methods will facilitate the investigations of other economically important algae species.

Secretomics: a biochemical footprinting tool for developing microalgal cultivation strategies.

Microalgae offer a promising source of biofuel and a wide array of high-value biomolecules. Large-scale cultivation of microalgae at low density poses a significant challenge in terms of water management. High-density microalgae cultivation, however, can be challenging due to biochemical changes associated with growth dynamics. Therefore, there is a need for a biomarker that can predict the optimum density for high biomass cultivation. A locally isolated microalga Cyanobacterium aponinum CCC734 was grown with optimized nitrogen and phosphorus in the ratio of 12:1 for sustained high biomass productivity. To understand density-associated bottlenecks secretome dynamics were monitored at biomass densities from 0.6 ± 0.1 to 7 ± 0.1 g/L (2 to 22 OD) in batch mode. Liquid chromatography coupled with mass spectrometry identified 880 exometabolites in the supernatant of C. aponinum CCC734. The PCA analysis showed similarity between exometabolite profiles at low (4 and 8 OD) and mid (12 and 16 OD), whereas distinctly separate at high biomass concentrations (20 and 22 OD). Ten exometabolites were selected based on their role in influencing growth and are specifically present at low, mid, and high biomass concentrations. Taking cues from secretome dynamics, 5.0 ± 0.5 g/L biomass concentration (16 OD) was optimal for C. aponinum CCC734 cultivation. Further validation was performed with a semi-turbidostat mode of cultivation for 29 days with a volumetric productivity of 1.0 ± 0.2 g/L/day. The secretomes-based footprinting tool is the first comprehensive growth study of exometabolite at the molecular level at variable biomass densities. This tool may be utilized in analyzing and directing microalgal cultivation strategies and reduction in overall operating costs.

Growth under Different Trophic Regimes and Synchronization of the Red Microalga Galdieria sulphuraria.

The extremophilic unicellular red microalga Galdieria sulphuraria (Cyanidiophyceae) is able to grow autotrophically, or mixo- and heterotrophically with 1% glycerol as a carbon source. The alga divides by multiple fission into more than two cells within one cell cycle. The optimal conditions of light, temperature and pH (500 µmol photons m-2 s-1, 40 °C, and pH 3; respectively) for the strain Galdieria sulphuraria (Galdieri) Merola 002 were determined as a basis for synchronization experiments. For synchronization, the specific light/dark cycle, 16/8 h was identified as the precondition for investigating the cell cycle. The alga was successfully synchronized and the cell cycle was evaluated. G. sulphuraria attained two commitment points with midpoints at 10 and 13 h of the cell cycle, leading to two nuclear divisions, followed subsequently by division into four daughter cells. The daughter cells stayed in the mother cell wall until the beginning of the next light phase, when they were released. Accumulation of glycogen throughout the cell cycle was also described. The findings presented here bring a new contribution to our general understanding of the cell cycle in cyanidialean red algae, and specifically of the biotechnologically important species G. sulphuraria.

Cytoklepty in the plankton: A host strategy to optimize the bioenergetic machinery of endosymbiotic algae.

Endosymbioses have shaped the evolutionary trajectory of life and remain ecologically important. Investigating oceanic photosymbioses can illuminate how algal endosymbionts are energetically exploited by their heterotrophic hosts and inform on putative initial steps of plastid acquisition in eukaryotes. By combining three-dimensional subcellular imaging with photophysiology, carbon flux imaging, and transcriptomics, we show that cell division of endosymbionts (Phaeocystis) is blocked within hosts (Acantharia) and that their cellular architecture and bioenergetic machinery are radically altered. Transcriptional evidence indicates that a nutrient-independent mechanism prevents symbiont cell division and decouples nuclear and plastid division. As endosymbiont plastids proliferate, the volume of the photosynthetic machinery volume increases 100-fold in correlation with the expansion of a reticular mitochondrial network in close proximity to plastids. Photosynthetic efficiency tends to increase with cell size, and photon propagation modeling indicates that the networked mitochondrial architecture enhances light capture. This is accompanied by 150-fold higher carbon uptake and up-regulation of genes involved in photosynthesis and carbon fixation, which, in conjunction with a ca.15-fold size increase of pyrenoids demonstrates enhanced primary production in symbiosis. Mass spectrometry imaging revealed major carbon allocation to plastids and transfer to the host cell. As in most photosymbioses, microalgae are contained within a host phagosome (symbiosome), but here, the phagosome invaginates into enlarged microalgal cells, perhaps to optimize metabolic exchange. This observation adds evidence that the algal metamorphosis is irreversible. Hosts, therefore, trigger and benefit from major bioenergetic remodeling of symbiotic microalgae with potential consequences for the oceanic carbon cycle. Unlike other photosymbioses, this interaction represents a so-called cytoklepty, which is a putative initial step toward plastid acquisition.

Make microalgal cultures axenic again - a fast and simple workflow utilizing fluorescence-activated cell sorting.

Since the removal of contaminations in microalgal cultures is extremely laborious and time-consuming, we developed a rapid workflow to obtain axenicity by a combination of fluorescence-activated cell sorting (FACS) and plate spreading. During method development, several cyanobacteria and green algae strains were successfully made axenic. At the end, method transferability to another FACS device was demonstrated. Our workflow offers great time-savings with less hands-on laboratory work compared to conventional isolation techniques.

Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo-production systems.

Light attenuation is a primary challenge limiting the upscaling of photobioreactors for sustainable bio-production. One key to this challenge, is to model and optimise the light/dark cycles so that cells within the dark region can be frequently transferred to the light region for photosynthesis. Therefore, this study proposes the first mechanistic model to integrate the light/dark cycle effects into biomass growth kinetics. This model was initially constructed through theoretical derivation based on the intracellular reaction kinetics, and was subsequently modified by embedding a new parameter, effective light coefficient, to account for the effects of culture mixing. To generate in silico process data, a new multiscale reactive transport modelling strategy was developed to couple fluid dynamics with biomass growth kinetics and light transmission. By comparing against previous experimental and computational studies, the multiscale model shows to be of high accuracy. Based on its simulation result, an original correlation was proposed to link effective light coefficient with photobioreactor gas inflow rate; this has not been done before. The impact of this study is that by using the proposed mechanistic model and correlation, we can easily control and optimise photobioreactor gas inflow rates to alleviate light attenuation and maintain a high biomass growth rate.

Double-high in palmitic and oleic acids accumulation in a non-model green microalga, Messastrum gracile SE-MC4 under nitrate-repletion and -starvation cultivations.

Bioprospecting for biodiesel potential in microalgae primarily involves a few model species of microalgae and rarely on non-model microalgae species. Therefore, the present study determined changes in physiology, oil accumulation, fatty acid composition and biodiesel properties of a non-model microalga Messastrum gracile SE-MC4 in response to 12 continuous days of nitrate-starve (NS) and nitrate-replete (NR) conditions respectively. Under NS, the highest oil content (57.9%) was achieved despite reductions in chlorophyll content, biomass productivity and lipid productivity. However, under both NS and NR, palmitic acid and oleic acid remained as dominant fatty acids thus suggesting high potential of M. gracile for biodiesel feedstock consideration. Biodiesel properties analysis returned high values of cetane number (CN 61.9-64.4) and degree of unsaturation (DU 45.3-57.4) in both treatments. The current findings show the possibility of a non-model microalga to inherit superior ability over model species in oil accumulation for biodiesel development.

Effect of nitrate feeding strategies on lipid and biomass productivities in fed-batch cultures of Nannochloropsis gaditana.

Controlled nitrate feeding strategies for fed-batch cultures of microalgae were applied for the enhancement of lipid production and microalgal growth rates. In particular, in this study, the effect of nitrate feeding rates on lipid and biomass productivities in fed-batch cultures of Nannochloropsis gaditana were investigated using three feeding modes (i.e., pulse, continuous, and staged) and under two light variations on both lipid productivity and fatty acid compositions. Higher nitrate levels negatively affected lipid production in the study. Increasing the light intensity increased the lipid contents of the microalgae in all three fed-batch feeding modes. A maximum of 58.3% lipid- to dry weight ratio was achieved when using pulse-fed cultures at an illumination of 200 µmol photons m-2  s-1 and 10 mg/day of nitrate feeding. This condition also resulted in the maximum lipid productivity of 44.6 mg L-1  day-1 . The fatty acid compositions of the lipids consisted predominantly of long-chain fatty acids (C:16 and C:18) and accounted for 70% of the overall fatty acid methyl esters. Pulse feeding mode was found to significantly enhance the biomass and lipid production. The other two feeding modes (continuous and staged) were not ideal for lipid and biomass production. This study demonstrates the applicability of pulse feeding strategies in fed-batch cultures as an appropriate cultivation strategy that can increase both lipid accumulation and biomass production.

Mineral phosphorus drives glacier algal blooms on the Greenland Ice Sheet.

Melting of the Greenland Ice Sheet is a leading cause of land-ice mass loss and cryosphere-attributed sea level rise. Blooms of pigmented glacier ice algae lower ice albedo and accelerate surface melting in the ice sheet's southwest sector. Although glacier ice algae cause up to 13% of the surface melting in this region, the controls on bloom development remain poorly understood. Here we show a direct link between mineral phosphorus in surface ice and glacier ice algae biomass through the quantification of solid and fluid phase phosphorus reservoirs in surface habitats across the southwest ablation zone of the ice sheet. We demonstrate that nutrients from mineral dust likely drive glacier ice algal growth, and thereby identify mineral dust as a secondary control on ice sheet melting.

A practical approach for modelling the growth of microalgae with population balance equation.

Microalgae are versatile microorganisms with applications in food, energy and fine chemicals, among others. Modelling the dynamics of microalgae inside a photobioreactor is a convenient and inexpensive way to determine the concentration of cells over time. Numerous models have been developed in the literature, but only a few are able to give relevant biological information. Such information can then be used to further improve the production process. The objective of this work was to develop a model for the determination of microalgal dynamics inside a photobioreactor as a function of the environmental conditions, to retrieve the size-specific growth and division rates as well as the number of daughter cells. The results demonstrate how to evaluate the time needed for microalgae to complete a full life-cycle. Inexpensive laboratory-based procedures and mathematical modelling are combined for the determination of relevant biological parameters.

Cryopreservation of Algae.

Cryopreservation has been successfully used in the banking and maintenance of cultures of microorganisms, from bacteria to yeasts, since the onset of cryobiology. Biobanking of marine biological resources is crucial for development of scientific knowledge as researchers rely on guaranteed access to reliable, stable resources. Culture collections play a key role in the provision of marine biological resources as they ensure long-term ex situ storage of biological resources that are made available for public and private sector research and education. In this chapter, we provide protocols for cryopreservation of different types of algae cultures.

Characterization of Particle Movement and High-Resolution Separation of Microalgal Cells via Induced-Charge Electroosmotic Advective Spiral Flow.

Microalgae are renewable, sustainable, and economical sources of biofuels and are capable of addressing pressing global demand for energy security. However, two challenging issues to produce high-level biofuels are to separate promising algal strains and protect biofuels from contamination of undesired bacteria, which rely on an economical and high-resolution separation technology. Separation technology based on induced-charge electroosmotic (ICEO) vortices offers excellent promise in economical microalga separation for producing biofuels because of its reconfigurable and flexible profiles and sensitive and precise selectivity. In this work, a practical ICEO vortex device is developed to facilitate high-resolution isolation of rich-lipid microalgae for the first time. We investigate electrokinetic equilibrium states of particles and particle-fluid ICEO effect in binary-particle manipulation. Nanoparticle separation is performed to demonstrate the feasibility and resolution of this device, yielding clear separation. Afterward, we leverage this technology in isolation of Chlorella vulgaris from heterogeneous microalgae with the purity exceeding 96.4%. Besides, this platform is successfully engineered for the extraction of single-cell Oocystis sp., obtaining the purity surpassing 95.2%. Moreover, with modulating parameters, we isolate desired-cell-number Oocystis sp. enabling us to investigate proliferation mode and carry out transcriptome analyses of Oocystis sp. for high-quality neutral lipids. This platform can be extended directly to economically separate other biological micro/nanosamples to address pressing issues, involving energy security, environmental monitoring, and disease diagnosis.

Classification of marine microalgae using low-resolution Mueller matrix images and convolutional neural network.

In this paper, we used a convolutional neural network to study the classification of marine microalgae by using low-resolution Mueller matrix images. Mueller matrix images of 12 species of algae from 5 families were measured by a Mueller matrix microscopy with an LED light source at 514 nm wavelength. The data sets of seven resolution levels were generated by the bicubic interpolation algorithm. We conducted two groups of classification experiments; one group classified the algae into 12 classes according to species category, and the other group classified the algae into 5 classes according to family category. In each group of classification experiments, we compared the classification results of the Mueller matrix images with those of the first element (M11) images. The classification accuracy of Mueller matrix images declines gently with the decrease of image resolution, while the accuracy of M11 images declines sharply. The classification accuracy of Mueller matrix images is higher than that of M11 images at each resolution level. At the lowest resolution level, the accuracy of 12-class classification and 5-class classification of full Mueller matrix images is 29.89% and 35.83% higher than those of M11 images, respectively. In addition, we also found that the polarization information of different species had different contributions to the classification. These results show that the polarization information can greatly improve the classification accuracy of low-resolution microalgal images.

Classification, identification, and growth stage estimation of microalgae based on transmission hyperspectral microscopic imaging and machine learning.

A transmission hyperspectral microscopic imager (THMI) that utilizes machine learning algorithms for hyperspectral detection of microalgae is presented. The THMI system has excellent performance with spatial and spectral resolutions of 4 µm and 3 nm, respectively. We performed hyperspectral imaging (HSI) of three species of microalgae to verify their absorption characteristics. Transmission spectra were analyzed using principal component analysis (PCA) and peak ratio algorithms for dimensionality reduction and feature extraction, and a support vector machine (SVM) model was used for classification. The average accuracy, sensitivity and specificity to distinguish one species from the other two species were found to be 94.4%, 94.4% and 97.2%, respectively. A species identification experiment for a group of mixed microalgae in solution demonstrates the usability of the classification method. Using a random forest (RF) model, the growth stage in a phaeocystis growth cycle cultivated under laboratory conditions was predicted with an accuracy of 98.1%, indicating the feasibility to evaluate the growth state of microalgae through their transmission spectra. Experimental results show that the THMI system has the capability for classification, identification and growth stage estimation of microalgae, with strong potential for in-situ marine environmental monitoring and early warning detection applications.

Revision of Coelastrella (Scenedesmaceae, Chlorophyta) and first register of this green coccoid microalga for continental Norway.

A terrestrial green microalga was isolated at Ås, in Akershus County, Norway. The strain corresponded to a coccoid chlorophyte. Morphological characteristics by light and electron microscopy, in conjunction with DNA amplification and sequencing of the 18 s rDNA gene and ITS sequences, were used to identify the microalgae. The characteristics agree with those of the genus Coelastrella defined by Chodat, and formed a sister group with the recently described C. thermophila var. globulina. Coelastrella is a relatively small numbered genus that has not been observed in continental Norway before; there are no previous cultures available in collections of Norwegian strains. Gas chromatography analyses of the FAME-derivatives showed a high percentage of polyunsaturated fatty acids (44-45%) especially linolenic acid (C18:3n3; 30-34%). After the stationary phase, the cultures were able to accumulate several carotenoids as neoxanthin, pheophytin a, astaxanthin, canthaxanthin, lutein, and violaxanthin. Due to the scarcity of visual characters suitable for diagnostic purposes and the lack of DNA sequence information, there is a high possibility that species of this genus have been neglected in local environmental studies, even though it showed interesting properties for algal biotechnology.

Single-Cell Mass Spectrometry Analysis of Metabolites Facilitated by Cell Electro-Migration and Electroporation.

Single-cell metabolite analysis plays an important role in biological study. While mass spectrometry is a powerful tool for identification and quantitation of metabolites, the low absolute analyte amounts in single cell and difficulty in sampling represent significant challenges in single cell analysis. In this study, we developed an effective method with a simple sampling procedure for analyzing single cells. A single cell was driven to a capillary tip through electro-migration, followed by releasing the cell contents through electroporation, into a sealed small volume (∼1.5 pL) to prevent dilution. Subsequent mass spectrometry analysis was performed directly with nanoelectrospray ionization. This method was applied for analyzing a variety of cells and monitoring the metabolic changes in response to perturbed cell culturing conditions. This method opens a new avenue for easy and rapid analysis of single cells with high sensitivity.

Infrared spectroscopy as a tool to monitor interactions between nanoplastics and microalgae.

The unicellular photosynthetic organisms known as microalgae are becoming one of the most important models for aquatic system studies. Among them, Chlamydomonas reinhardtii is widely used as a bioindicator of pollution or of different changes in the environment. Numerous pollutants are present in aquatic environments, particularly plastics and nanoplastics. Physiological variations after an environmental change highlight variation in the macromolecular composition of microalgae (proteins, nucleic acids, lipids and carbohydrates). Recently, Fourier transform infrared vibrational spectroscopy has been described as a reliable tool, sensitive and allowing rapid measurement of macromolecular composition of microalgae. Coupled with preprocessing and principal component analysis, it is well adapted to monitoring the effect of environmental stress on biochemical composition. In this study, infrared spectroscopy, combined with multivariate analysis, has been tested first on known environmental stresses such as light intensity variation and nitrogen limitation. Then, this technique has been applied to monitor the interaction and potential impacts of polystyrene nanoparticles on microalgae. The results showed slight variations on protein and carbohydrates bands in the presence of nanoplastics, suggesting that their presence led to modifications in the biochemical composition of the microalgae. To confirm the interaction between microalgae and nanoplastics, visualization by confocal microscopy and cytotoxicity measurement has been carried out. Results showed that polystyrene nanoparticles seemed to adsorb on microalgae surface, leading to a loss of plasma membrane integrity. The resulting chemical modifications, even if moderate, could be detected by infrared spectroscopy' showing that this tool could be very helpful in the understanding of nanoparticle-microalgae interaction mechanisms.