Metagenomic analysis of microbial consortia native to the Amazon, Highlands, and Galapagos regions of Ecuador with potential for wastewater remediation.

Native microbial consortia have been proposed for biological wastewater treatment, but their diversity and function remain poorly understood. This study investigated three native microalgae-bacteria consortia collected from the Amazon, Highlands, and Galapagos regions of Ecuador to assess their metagenomes and wastewater remediation potential. The consortia were evaluated for 12 days under light (LC) and continuous dark conditions (CDC) to measure their capacity for nutrient and organic matter removal from synthetic wastewater (SWW). Overall, all three consortia demonstrated higher nutrient removal efficiencies under LC than CDC, with the Amazon and Galapagos consortia outperforming the Highlands consortium in nutrient removal capabilities. Despite differences in α- and ß-diversity, microbial species diversity within and between consortia did not directly correlate with their nutrient removal capabilities. However, all three consortia were enriched with core taxonomic groups associated with wastewater remediation activities. Our analyses further revealed higher abundances for nutrient removing microorganisms in the Amazon and Galapagos consortia compared with the Highland consortium. Finally, this study also uncovered the contribution of novel microbial groups that enhance wastewater bioremediation processes. These groups have not previously been reported as part of the core microbial groups commonly found in wastewater communities, thereby highlighting the potential of investigating microbial consortia isolated from ecosystems of megadiverse countries like Ecuador.

Refining taxonomic identification of microalgae through molecular and genetic evolution: a case study of Prorocentrum lima and Prorocentrum arenarium.

Species delimitation based on lineage definition has become increasingly popular. However, these methods have been limited, especially for species that lack genomic data and are morphologically similar. The trickiest part for the species identification is that the interspecific and intraspecific boundaries are vague. Taking Prorocentrum (Dinophyta) as an example, analysis of cell morphology, growth, and toxin synthesis in both species of P. lima and P. arenarium does not provide a reliable basis for species delineation. However, through phylogenetic and genetic distance analyses of their ITS and LSU sequences, establishment of evolutionary tree based on orthologous gene sequences, and combining the results of automatic barcode gap discovery and Poisson tree processes models, it was sustained that P. arenarium does not belong to the P. lima complex and should be considered as an independent species. Interspecies genetic evolution analysis revealed that P. lima and P. arenarium may contribute to evolutionary direction that favors combating reverse environmental factors. In P. lima, viral invasion may be one of the reasons for its large genome size. In the study, P. lima complex has been selected as an example to enhance the taxonomic identification of microalgae through molecular and genetic evolution, offering valuable insights into refining taxonomic identification and promoting microbial biodiversity research in other species.IMPORTANCEMicroalgae, especially the species known as Prorocentrum, have received significant attention due to their ability to trigger harmful algal blooms and produce toxins. However, the boundaries between species and within species are ambiguous. Clear and comprehensive species delineation indicates that Prorocentrum arenarium should be considered as an independent species, separate from the Prorocentrum lima complex. Improving the classification and identification of microalgae through molecular and genetic evolution will provide reference points for other cryptic species. Prorocentrum occupy multiple ecological niches in marine environments, and studying their evolutionary direction contributes to understanding their ecological adaptations and community succession.

Use of microalgal biomass as functional ingredient for preparation of cereal based extrudates: impact of processing on amino acid concentrations and colour degradation kinetics

Abstract Suitability of developing Spirulina incorporated cereal based low cost nutritious extrudates was analysed against extrusion processing parameters. Most significant extrusion processing parameters considered for present study were feed moisture (20-25%), die temperature (100-120 °C) and screw speed (50-100 rpm). Different extrusion conditions were used to obtain most acceptable rice: Spirulina blend extrudates. In present study before extrusion processing different additives (citric acid and sodium bicarbonate) were added in rice: Spirulina blend and checked its effect on colour degradation kinetics at varied packaging and storage conditions. Higher screw speed (100 rpm) indicating less residence time of feed material inside the barrel resulted in higher colour retention of rice: Spirulina (97:03) blend extrudates. Kinetics for rice: Spirulina (97:03) blend extrudates indicates faster rate of colour degradation in terms of lightness (half-life of 4 days) when packed in metalized polyethylene at 50°C with 65% relative humidity. Increased concentration of Spirulina (1-3%) in raw formulations resulted in increase in concentration of all amino acids. Impact of extrusion processing has shown non-significant (p ≤ 0.05) effect on amino acid concentrations of rice: Spirulina blend extrudates. Also, all the spirulina added samples showed good consumer acceptability with the score of 6.7

Genome-based identification and comparative analysis of enzymes for carotenoid biosynthesis in microalgae.

Microalgae are potential feedstocks for the commercial production of carotenoids, however, the metabolic pathways for carotenoid biosynthesis across algal lineage are largely unexplored. This work is the first to provide a comprehensive survey of genes and enzymes associated with the less studied methylerythritol 4-phosphate/1-deoxy-D-xylulose 5-phosphate pathway as well as the carotenoid biosynthetic pathway in microalgae through bioinformatics and comparative genomics approach. Candidate genes/enzymes were subsequently analyzed across 22 microalgae species of lineages Chlorophyta, Rhodophyta, Heterokonta, Haptophyta, Cryptophyta, and known Arabidopsis homologs in order to study the evolutional divergence in terms of sequence-structure properties. A total of 403 enzymes playing a vital role in carotene, lutein, zeaxanthin, violaxanthin, canthaxanthin, and astaxanthin were unraveled. Of these, 85 were hypothetical proteins whose biological roles are not yet experimentally characterized. Putative functions to these hypothetical proteins were successfully assigned through a comprehensive investigation of the protein family, motifs, intrinsic physicochemical features, subcellular localization, pathway analysis, etc. Furthermore, these enzymes were categorized into major classes as per the conserved domain and gene ontology. Functional signature sequences were also identified which were observed conserved across microalgal genomes. Additionally, the structural modeling and active site architecture of three vital enzymes, DXR, PSY, and ZDS catalyzing the vital rate-limiting steps in Dunaliella salina were achieved. The enzymes were confirmed to be stereochemically reliable and stable as revealed during molecular dynamics simulation of 100 ns. The detailed functional information about individual vital enzymes will certainly help to design genetically modified algal strains with enhanced carotenoid contents.

Confocal hyperspectral microscopic imager for the detection and classification of individual microalgae.

We propose a confocal hyperspectral microscopic imager (CHMI) that can measure both transmission and fluorescent spectra of individual microalgae, as well as obtain classical transmission images and corresponding fluorescent hyperspectral images with a high signal-to-noise ratio. Thus, the system can realize precise identification, classification, and location of microalgae in a free or symbiosis state. The CHMI works in a staring state, with two imaging modes, a confocal fluorescence hyperspectral imaging (CFHI) mode and a transmission hyperspectral imaging (THI) mode. The imaging modes share the main light path, and thus obtained fluorescence and transmission hyperspectral images have point-to-point correspondence. In the CFHI mode, a confocal technology to eliminate image blurring caused by interference of axial points is included. The CHMI has excellent performance with spectral and spatial resolutions of 3 nm and 2 µm, respectively (using a 10× microscope objective magnification). To demonstrate the capacity and versatility of the CHMI, we report on demonstration experiments on four species of microalgae in free form as well as three species of jellyfish with symbiotic microalgae. In the microalgae species classification experiments, transmission and fluorescence spectra collected by the CHMI were preprocessed using principal component analysis (PCA), and a support vector machine (SVM) model or deep learning was then used for classification. The accuracy of the SVM model and deep learning method to distinguish one species of individual microalgae from another was found to be 96.25% and 98.34%, respectively. Also, the ability of the CHMI to analyze the concentration, species, and distribution differences of symbiotic microalgae in symbionts is furthermore demonstrated.

The biogeographic differentiation of algal microbiomes in the upper ocean from pole to pole.

Eukaryotic phytoplankton are responsible for at least 20% of annual global carbon fixation. Their diversity and activity are shaped by interactions with prokaryotes as part of complex microbiomes. Although differences in their local species diversity have been estimated, we still have a limited understanding of environmental conditions responsible for compositional differences between local species communities on a large scale from pole to pole. Here, we show, based on pole-to-pole phytoplankton metatranscriptomes and microbial rDNA sequencing, that environmental differences between polar and non-polar upper oceans most strongly impact the large-scale spatial pattern of biodiversity and gene activity in algal microbiomes. The geographic differentiation of co-occurring microbes in algal microbiomes can be well explained by the latitudinal temperature gradient and associated break points in their beta diversity, with an average breakpoint at 14 °C ± 4.3, separating cold and warm upper oceans. As global warming impacts upper ocean temperatures, we project that break points of beta diversity move markedly pole-wards. Hence, abrupt regime shifts in algal microbiomes could be caused by anthropogenic climate change.

Algal glycobiotechnology: omics approaches for strain improvement.

Microalgae has the capability to replace petroleum-based fuels and is a promising option as an energy feedstock because of its fast growth, high photosynthetic capacity and remarkable ability to store energy reserve molecules in the form of lipids and starch. But the commercialization of microalgae based product is difficult due to its high processing cost and low productivity. Higher accumulation of these molecules may help to cut the processing cost. There are several reports on the use of various omics techniques to improve the strains of microalgae for increasing the productivity of desired products. To effectively use these techniques, it is important that the glycobiology of microalgae is associated to omics approaches to essentially give rise to the field of algal glycobiotechnology. In the past few decades, lot of work has been done to improve the strain of various microalgae such as Chlorella, Chlamydomonas reinhardtii, Botryococcus braunii etc., through genome sequencing and metabolic engineering with major focus on significantly increasing the productivity of biofuels, biopolymers, pigments and other products. The advancements in algae glycobiotechnology have highly significant role to play in innovation and new developments for the production algae-derived products as above. It would be highly desirable to understand the basic biology of the products derived using -omics technology together with biochemistry and biotechnology. This review discusses the potential of different omic techniques (genomics, transcriptomics, proteomics, metabolomics) to improve the yield of desired products through algal strain manipulation.

Inelastic hyperspectral Scheimpflug lidar for microalgae classification and quantification.

An inelastic hyperspectral Scheimpflug lidar system was developed for microalgae classification and quantification. The correction for the refraction at the air-glass-water interface was established, making our system suitable for aquatic environments. The fluorescence spectrum of microalgae was extracted by principal component analysis, and seven species of microalgae from different phyla have been classified. It was verified that when the cell density of Phaeocystis globosa was in the range of ${{1}}{{{0}}^4}\sim{{1}}{{{0}}^6}\;{\rm{cell}}\;{\rm{m}}{{\rm{L}}^{- 1}}$, the cell density had a linear relationship with the fluorescence intensity. The experimental results show our system can identify and quantify microalgae, with application prospects for microalgae monitoring in the field environment and early warning of red tides or algal blooms.

Predicting population genetic change in an autocorrelated random environment: Insights from a large automated experiment.

Most natural environments exhibit a substantial component of random variation, with a degree of temporal autocorrelation that defines the color of environmental noise. Such environmental fluctuations cause random fluctuations in natural selection, affecting the predictability of evolution. But despite long-standing theoretical interest in population genetics in stochastic environments, there is a dearth of empirical estimation of underlying parameters of this theory. More importantly, it is still an open question whether evolution in fluctuating environments can be predicted indirectly using simpler measures, which combine environmental time series with population estimates in constant environments. Here we address these questions by using an automated experimental evolution approach. We used a liquid-handling robot to expose over a hundred lines of the micro-alga Dunaliella salina to randomly fluctuating salinity over a continuous range, with controlled mean, variance, and autocorrelation. We then tracked the frequencies of two competing strains through amplicon sequencing of nuclear and choloroplastic barcode sequences. We show that the magnitude of environmental fluctuations (determined by their variance), but also their predictability (determined by their autocorrelation), had large impacts on the average selection coefficient. The variance in frequency change, which quantifies randomness in population genetics, was substantially higher in a fluctuating environment. The reaction norm of selection coefficients against constant salinity yielded accurate predictions for the mean selection coefficient in a fluctuating environment. This selection reaction norm was in turn well predicted by environmental tolerance curves, with population growth rate against salinity. However, both the selection reaction norm and tolerance curves underestimated the variance in selection caused by random environmental fluctuations. Overall, our results provide exceptional insights into the prospects for understanding and predicting genetic evolution in randomly fluctuating environments.

Whole Alga, Algal Extracts, and Compounds as Ingredients of Functional Foods: Composition and Action Mechanism Relationships in the Prevention and Treatment of Type-2 Diabetes Mellitus.

Type-2 diabetes mellitus (T2DM) is a major systemic disease which involves impaired pancreatic function and currently affects half a billion people worldwide. Diet is considered the cornerstone to reduce incidence and prevalence of this disease. Algae contains fiber, polyphenols, ω-3 PUFAs, and bioactive molecules with potential antidiabetic activity. This review delves into the applications of algae and their components in T2DM, as well as to ascertain the mechanism involved (e.g., glucose absorption, lipids metabolism, antioxidant properties, etc.). PubMed, and Google Scholar databases were used. Papers in which whole alga, algal extracts, or their isolated compounds were studied in in vitro conditions, T2DM experimental models, and humans were selected and discussed. This review also focuses on meat matrices or protein concentrate-based products in which different types of alga were included, aimed to modulate carbohydrate digestion and absorption, blood glucose, gastrointestinal neurohormones secretion, glycosylation products, and insulin resistance. As microbiota dysbiosis in T2DM and metabolic alterations in different organs are related, the review also delves on the effects of several bioactive algal compounds on the colon/microbiota-liver-pancreas-brain axis. As the responses to therapeutic diets vary dramatically among individuals due to genetic components, it seems a priority to identify major gene polymorphisms affecting potential positive effects of algal compounds on T2DM treatment.

The Under-explored Extracellular Proteome of Aero-Terrestrial Microalgae Provides Clues on Different Mechanisms of Desiccation Tolerance in Non-Model Organisms.

Trebouxia sp. (TR9) and Coccomyxa simplex (Csol) are desiccation-tolerant lichen microalgae with different adaptive strategies in accordance with the prevailing conditions of their habitats. The remodelling of cell wall and extracellular polysaccharides depending on water availability are key elements in the tolerance to desiccation of both microalgae. Currently, there is no information about the extracellular proteins of these algae and other aero-terrestrial microalgae in response to limited water availability. To our knowledge, this is the first report on the proteins associated with the extracellular polymeric substances (EPS) of aero-terrestrial microalgae subjected to cyclic desiccation/rehydration. LC-MS/MS and bioinformatic analyses of the EPS-associated proteins in the two lichen microalgae submitted to four desiccation/rehydration cycles allowed the compilation of 111 and 121 identified proteins for TR9 and Csol, respectively. Both sets of EPS-associated proteins shared a variety of predicted biological functions but showed a constitutive expression in Csol and partially inducible in TR9. In both algae, the EPS-associated proteins included a number of proteins of unknown functions, some of which could be considered as small intrinsically disordered proteins related with desiccation-tolerant organisms. Differences in the composition and the expression pattern between the studied EPS-associated proteins would be oriented to preserve the biochemical and biophysical properties of the extracellular structures under the different conditions of water availability in which each alga thrives.

Adaptive Evolution Improves Algal Strains for Environmental Remediation.

Microalgae have potential for environmental remediation, but they must better tolerate stress. Adaptive laboratory evolution (ALE) is effective to construct evolved strains, but its efficiency is low. Highly efficient ALE relies on selecting suitable environmental stress, original strain selection, and optimizing initial cell density and stress strategy.

Domestication via the commensal pathway in a fish-invertebrate mutualism.

Domesticator-domesticate relationships are specialized mutualisms where one species provides multigenerational support to another in exchange for a resource or service, and through which both partners gain an advantage over individuals outside the relationship. While this ecological innovation has profoundly reshaped the world's landscapes and biodiversity, the ecological circumstances that facilitate domestication remain uncertain. Here, we show that longfin damselfish (Stegastes diencaeus) aggressively defend algae farms on which they feed, and this protective refuge selects a domesticator-domesticate relationship with planktonic mysid shrimps (Mysidium integrum). Mysids passively excrete nutrients onto farms, which is associated with enriched algal composition, and damselfish that host mysids exhibit better body condition compared to those without. Our results suggest that the refuge damselfish create as a byproduct of algal tending and the mutual habituation that damselfish and mysids exhibit towards one another were instrumental in subsequent mysid domestication. These results are consistent with domestication via the commensal pathway, by which many common examples of animal domestication are hypothesized to have evolved.

Effects of sponge-derived Ageladine A on the photosynthesis of different microalgal species and strains.

Fluorescent natural compounds have been identified in several marine hosts of microalgae. Their prevalence, and the energy the host is expending on their synthesis, suggests an important, yet poorly understood ecological role. It has been suggested that some of these natural products may enhance the photosynthesis of microbial symbionts. In this study, the effect of Ageladine A (Ag A), a pH-dependent fluorophore found in sponges of the genus Agelas, on the photosynthesis of nine microalgal species and strains was examined. The data showed that the variety of effects of Ag A additions differed between species, and even strains within a species. While in one strain of Synechococcus sp., the presence of Ag A increased gross photosynthesis under UV light exposure, it decreased in another. And while in the chlorophyte T. chuii overall metabolic activity was greatly reduced under all forms of lighting, photosynthesis in T. lutea was positively affected by the addition of Ag A. The variety of effects of Ag A on photosynthesis observed in this study indicate a complex interaction of Ag A with microalgal cells and suggests that a host may be able to shape its own symbiotic microbiome with self-produced natural products.

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.

The first characterization of airborne cyanobacteria and microalgae in the Adriatic Sea region.

The presence of airborne cyanobacteria and microalgae as well as their negative impacts on human health have been documented by many researchers worldwide. However, studies on cyanobacteria and microalgae are few compared with those on bacteria and viruses. Research is especially lacking on the presence and taxonomic composition of cyanobacteria and microalgae near economically important water bodies with much tourism, such as the Adriatic Sea region. Here, we present the first characterization of the airborne cyanobacteria and microalgae in this area. Sampling conducted between 11th and 15th June 2017 revealed a total of 15 taxa of airborne cyanobacteria and microalgae. Inhalation of many of the detected taxa, including Synechocystis sp., Synechococcus sp., Bracteacoccus sp., Chlorella sp., Chlorococcum sp., Stichococcus sp., and Amphora sp., poses potential threats to human health. Aside from two green algae, all identified organisms were capable of producing harmful metabolites, including toxins. Moreover, we documented the presence of the cyanobacterium Snowella sp. and the green alga Tetrastrum sp., taxa that had not been previously documented in the atmosphere by other researchers. Our study shows that the Adriatic Sea region seems to be a productive location for future research on airborne cyanobacteria and microalgae in the context of their impacts on human health, especially during the peak of tourism activity.

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.

Total Lipids Content, Lipid Class and Fatty Acid Composition of Ten Species of Microalgae.

Microalgae is a potential producer of functional lipids such as n-3 polyunsaturated fatty acids (PUFA) and fucoxanthin. In the present study, lipids from ten microalgae species were analyzed especially focusing on the fucoxanthin, lipid and fatty acid compositions. The study revealed a remarkable variation in total lipids content, fucoxanthin content, lipid class composition and n-3 PUFA content in individual species, although they belong to the same genus. Among microalgae examined, Pavlova lutheri contained the highest total lipids content (313.59 mg g-1 dry weight) and considerable amount of fucoxanthin (3.13 mg g-1 dry weight). It also had the highest level (28.01%) of total n-3 PUFA with high level of eicosapentaenoic acid (EPA) (17.76%) and docosahexaenoic acid (DHA) (7.61%). The highest fucoxanthin content (5.19 mg g-1 dry weight) was observed in Chaetoceros gracilis. C. gracilis also contained relatively high level of total lipids (228.87 mg g-1 dry weight) and 10.67% EPA. The results also demonstrated that Nannochloropsis oculata contained the greatest amount of EPA (26.21%), while Isochrysis galbana had the highest level of DHA (8.76%). And both microalgae contained 1.71 and 4.44 mg g-1 dry weight fucoxanthin, respectively. Microalgal lipids containing abundant fucoxanthin and n-3 PUFA such as EPA and DHA in the present study will be used as nutraceutical lipids with great commercial potential.

Efficient open cultivation of cyanidialean red algae in acidified seawater.

Microalgae possess high potential for producing pigments, antioxidants, and lipophilic compounds for industrial applications. However, their open pond cultures are often contaminated by other undesirable organisms, including their predators. In addition, the cost of using freshwater is relatively high, which limits the location and scale of cultivation compared with using seawater. It was previously shown that Cyanidium caldarium and Galdieria sulphuraria, but not Cyanidioschyzon merolae grew in media containing NaCl at a concentration equivalent to seawater. We found that the preculture of C. merolae in the presence of a moderate NaCl concentration enabled the cells to grow in the seawater-based medium. The cultivation of cyanidialean red algae in the seawater-based medium did not require additional pH buffering chemicals. In addition, the combination of seawater and acidic conditions reduced the risk of contamination by other organisms in the nonsterile open culture of C. merolae more efficiently than the acidic condition alone.