RNA-Seq and metabolic flux analysis of Tetraselmis sp. M8 during nitrogen starvation reveals a two-stage lipid accumulation mechanism

Tetraselmis species for environmental sustainability: biology, water bioremediation, and biofuel production

With increasing demand of fossil fuels and water pollution and their environmental impacts, marine green microalgae have gained special attention in both scientific and industrial  fields. This is due to their fast growth in non-arable lands with high photosynthetic activity, their metabolic plasticity, as well as their high CO2 capture capacity. Tetraselmis species, green and eukaryotic microalgae, are not only considered as a valuable source of biomolecules including pigments, lipids, and starch but also widely used in biotechnological applications. Tetraselmis cultivation for high-value biomolecules and industrial use was demonstrated to be a non-cost-effective strategy because of its low demand in nutrients, such as phosphorus and nitrogen. Recently, phycoremediation of wastewater rich in nutrients, chemicals, and heavy metals has become an efficient and economic-alternative that allows the detoxification of waters and induces mechanisms in algal cells for biomolecules rich-energy synthesis to regulate their metabolic pathways. This review aims to shed light on Tetraselmis species for their different culture conditions and metabolites bioaccumulation, as well as their human health and environmental applications. Additionally, phycoremediation of contaminants associated to biofuel production in Tetraselmis cells and their different intracellular and extracellular mechanisms have also been investigated.

A critical review of machine-learning for "multi-omics" marine metabolite datasets

During the last decade, genomic, transcriptomic, proteomic, metabolomic, and other omics datasets have been generated for a wide range of marine organisms, and even more are still on the way. Marine organisms possess unique and diverse biosynthetic pathways contributing to the synthesis of novel secondary metabolites with significant bioactivities. As marine organisms have a greater tendency to adapt to stressed environmental conditions, the chance to identify novel bioactive metabolites with potential biotechnological application is very high. This review presents a comprehensive overview of the available "-omics" and "multi-omics" approaches employed for characterizing marine metabolites along with novel data integration tools. The need for the development of machine-learning algorithms for "multi-omics" approaches is briefly discussed. In addition, the challenges involved in the analysis of "multi-omics" data and recommendations for conducting "multi-omics" study were discussed.

Proteomic analysis reveals mechanisms of mixed wastewater with different N/P ratios affecting the growth and biochemical characteristics of Chlorella pyrenoidosa

Effects of different nutrient ratios on the biochemical compositions of microalgae and the changes were rarely studied at the molecular level. In this study, the impacts of various nitrogen to phosphorus (N/P) ratios on growing of C. pyrenoidosa, as well as biochemical compositions and the metabolic regulation mechanism in mixed sewage, were investigated. The results suggested that 18 was optimal N/P ratio, while the dry weight (1.0 g/L), chlorophyll-a (Chla) (3.63 mg/L), and lipid production (0.28 g/L) were all the highest comparing with other groups. In contrast, the protein production (0.37 g/L) was the least. The nature of the regulatory mechanisms inthe metabolic pathways of these biochemical compositions was revealed by proteomic results, and there were 62 different expression proteins (DEPs) taken part in fatty acid and lipid biosynthesis metabolism (FA), amino acid biosynthesis metabolism (AA), photosynthesis (PHO), carbon fixation in photosynthetic organisms (CFP), and central carbon metabolism (CCM).

Trends in digital image processing of isolated microalgae by incorporating classification algorithm

Identification of microalgae species is of importance due to the uprising of harmful algae blooms affecting both the aquatic habitat and human health. Despite this occurence, microalgae have been identified as a green biomass and alternative source due to its promising bioactive compounds accumulation that play a significant role in many industrial applications. Recently, microalgae species identification has been conducted through DNA analysis and various microscopy techniques such as light, scanning electron, transmission electron, and atomic force -microscopy. The aforementioned procedures have encouraged researchers to consider alternate ways due to limitations such as costly validation, requiring skilled taxonomists, prolonged analysis, and low accuracy. This review highlights the potential innovations in digital microscopy with the incorporation of both hardware and software that can produce a reliable recognition, detection, enumeration, and real-time acquisition of microalgae species. Several steps such as image acquisition, processing, feature extraction, and selection are discussed, for the purpose of generating high image quality by removing unwanted artifacts and noise from the background. These steps of identification of microalgae species is performed by reliable image classification through machine learning as well as deep learning algorithms such as artificial neural networks, support vector machines, and convolutional neural networks. Overall, this review provides comprehensive insights into numerous possibilities of microalgae image identification, image pre-processing, and machine learning techniques to address the challenges in developing a robust digital classification tool for the future.

Advances in engineering algae for biofuel production

While algae demonstrate potential as a sustainable fuel source, low productivities limit the economic realization of algal biofuels. High-throughput strain engineering, omics-informed genome-scale modeling, and microbiome engineering are key technologies for enabling algal biofuels. High-throughput strain engineering efforts generate improved traits, including high biomass productivity and lipid content, in diverse algal species. Genome-scale models, constructed with the aid of omics data, provide insight into metabolic limitations and guide rational algal strain engineering efforts. As outdoor cultivation systems introduce exogenous organisms, microbiome engineering seeks to eliminate harmful organisms and introduce beneficial species. Optimizing algal biomass production and lipid content using these technologies may overcome the productivity barrier for the commercialization of algal biofuels.

Integrated Viral Elements Suggest the Dual Lifestyle of Tetraselmis Spp. Polinton-Like Viruses

In this study, we aimed at exploring horizontal gene transfer between viruses and Chlorodendraceae green algae (Chlorophyta) using available genomic and transcriptomic sequences for twenty algal strains. We identified a significant number of genes sharing a higher sequence similarity with viral homologues, thus signalling their possible involvement in horizontal gene transfers with viruses. Further characterization showed that many of these genes were clustered in DNA regions of several tens to hundreds of kilobases in size, originally belonging to viruses related to known Tetraselmis spp. viruses (TetV and TsV). In contrast, the remaining candidate HGT genes were randomly dispersed in the algal genomes, were more frequently transcribed, and belonged to large multigene families. The presence of homologues in Viridiplantae suggested that the latter were more likely of algal rather than viral origin. We found a remarkable diversity in polinton-like virus (PLV) elements inserted in Tetraselmis genomes, all of which were most similar to the Tetraselmis striata virus (TsV). The genes of PLV elements are transcriptionally inactive with the notable exception of the homologue of the TVSG_00024 gene of TsV whose function is unknown. We suggest that this gene may be involved in a sentinel process to trigger virus reactivation and excision in response to an environmental stimulus. Altogether, these results provide evidence that TsV-related viruses have a dual lifestyle, alternating between a free viral phase (i.e. virion) and a phase integrated into host genomes.

Metabolic pathways for biosynthesis and degradation of starch in Tetraselmis chui during nitrogen deprivation and recovery

Tetraselmis chui is known to accumulate starch when subjected to stress. This phenomenon is widely studied for the purpose of industrial production and process development. Yet, knowledge about the metabolic pathways involved is still immature. Hence, in this study, transcription of 27 starch-related genes was monitored under nitrogen deprivation and resupply in 25 L tubular photobioreactors. T. chui proved to be an efficient starch producer under nitrogen deprivation, accumulating starch up to 56% of relative biomass content. The prolonged absence of nitrogen led to an overall down-regulation of the tested genes, in most instances maintained even after nitrogen replenishment when starch was actively degraded. These gene expression patterns suggest post-transcriptional regulatory mechanisms play a key role in T. chui under nutrient stress. Finally, the high productivity combined with an efficient recovery after nitrogen restitution makes this species a suitable candidate for industrial production of high-starch biomass.

Biosynthesis and biotechnological interventions for commercial production of microalgal pigments: A review

Microalgae are photosynthetic eukaryotes that serve as microbial cell factories for the production of useful biochemicals, including pigments. These pigments are eco-friendly alternatives to synthetic dyes and reduce environmental and health risks. They also exhibit excellent anti-oxidative properties, making them a useful commodity in the nutrition and pharmaceutical industries. Light-harvesting pigments such as chlorophylls and phycobilins, and photoprotective carotenoids are some of the most common microalgal pigments. The increasing demand for these pigments in industrial applications has prompted a need to improve their metabolic yield in microalgal cells. So far, expensive cultivation methods and sensitivity to microbial contamination remain the main obstacles to the large-scale production of these pigments. This review highlights current issues and future prospects related to the production of microalgal pigments. The review also emphasizes the use of engineering approaches such as genetic engineering, and optimization of media components and physical parameters to increase their commercial-scale production.

Function of ORFC of the polyketide synthase gene cluster on fatty acid accumulation in Schizochytrium limacinum SR21

BACKGROUND

As a potential source of polyunsaturated fatty acids (PUFA), Schizochytrium sp. has been widely used in industry for PUFA production. Polyketide synthase (PKS) cluster is supposed to be the primary way of PUFA synthesis in Schizochytrium sp. As one of three open reading frames (ORF) in the PKS cluster, ORFC plays an essential role in fatty acid biosynthesis. However, the function of domains in ORFC in the fatty acid synthesis of Schizochytrium sp. remained unclear.

RESULTS

In this study, heterologous expression and overexpression were carried out to study the role of ORFC and its domains in fatty acid accumulation. Firstly, ORFC was heterologously expressed in yeast which increased the PUFA content significantly. Then, the dehydratase (DH) and enoyl reductase (ER) domains located on ORFC were overexpressed in Schizochytrium limacinum SR21, respectively. Fatty acids profile analysis showed that the contents of PUFA and saturated fatty acid were increased in the DH and ER overexpression strains, respectively. This indicated that the DH and ER domains played distinct roles in lipid accumulation. Metabolic and transcriptomic analysis revealed that the pentose phosphate pathway and triacylglycerol biosynthesis were enhanced, while the tricarboxylic acid cycle and fatty acids oxidation were weakened in DH-overexpression strain. However, the opposite effect was found in the ER-overexpression strain.

CONCLUSION

Therefore, ORFC was required for the biosynthesis of fatty acid. The DH domain played a crucial role in PUFA synthesis, whereas the ER domain might be related to saturated fatty acids (SFA) synthesis in Schizochytrium limacinum SR21. This research explored the role of ORFC in the PKS gene cluster in Schizochytrium limacinum and provided potential genetic modification strategies for improving lipid production and regulating PUFA and SFA content.

Comprehensive Utilization of Marine Microalgae for Enhanced Co-Production of Multiple Compounds

Marine microalgae are regarded as potential feedstock because of their multiple valuable compounds, including lipids, pigments, carbohydrates, and proteins. Some of these compounds exhibit attractive bioactivities, such as carotenoids, ω-3 polyunsaturated fatty acids, polysaccharides, and peptides. However, the production cost of bioactive compounds is quite high, due to the low contents in marine microalgae. Comprehensive utilization of marine microalgae for multiple compounds production instead of the sole product can be an efficient way to increase the economic feasibility of bioactive compounds production and improve the production efficiency. This paper discusses the metabolic network of marine microalgal compounds, and indicates their interaction in biosynthesis pathways. Furthermore, potential applications of co-production of multiple compounds under various cultivation conditions by shifting metabolic flux are discussed, and cultivation strategies based on environmental and/or nutrient conditions are proposed to improve the co-production. Moreover, biorefinery techniques for the integral use of microalgal biomass are summarized. These techniques include the co-extraction of multiple bioactive compounds from marine microalgae by conventional methods, super/subcritical fluids, and ionic liquids, as well as direct utilization and biochemical or thermochemical conversion of microalgal residues. Overall, this review sheds light on the potential of the comprehensive utilization of marine microalgae for improving bioeconomy in practical industrial application.

Transcriptome Analysis Reveals the Molecular Mechanisms Underlying Adenosine Biosynthesis in Anamorph Strain of Caterpillar Fungus

Caterpillar fungus is a well-known fungal Chinese medicine. To reveal molecular changes during early and late stages of adenosine biosynthesis, transcriptome analysis was performed with the anamorph strain of caterpillar fungus. A total of 2,764 differentially expressed genes (DEGs) were identified (p ≤ 0.05, |log₂ Ratio| ≥ 1), of which 1,737 were up-regulated and 1,027 were down-regulated. Gene expression profiling on 4–10 d revealed a distinct shift in expression of the purine metabolism pathway. Differential expression of 17 selected DEGs which involved in purine metabolism (map00230) were validated by qPCR, and the expression trends were consistent with the RNA-Seq results. Subsequently, the predicted adenosine biosynthesis pathway combined with qPCR and gene expression data of RNA-Seq indicated that the increased adenosine accumulation is a result of down-regulation of ndk, ADK, and APRT genes combined with up-regulation of AK gene. This study will be valuable for understanding the molecular mechanisms of the adenosine biosynthesis in caterpillar fungus.

Marine Natural Products from Microalgae: An -Omics Overview

Over the last decade, genome sequences and other -omics datasets have been produced for a wide range of microalgae, and several others are on the way. Marine microalgae possess distinct and unique metabolic pathways, and can potentially produce specific secondary metabolites with biological activity (e.g., antipredator, allelopathic, antiproliferative, cytotoxic, anticancer, photoprotective, as well as anti-infective and antifouling activities). Because microalgae are very diverse, and adapted to a broad variety of environmental conditions, the chances to find novel and unexplored bioactive metabolites with properties of interest for biotechnological and biomedical applications are high. This review presents a comprehensive overview of the current efforts and of the available solutions to produce, explore and exploit -omics datasets, with the aim of identifying species and strains with the highest potential for the identification of novel marine natural products. In addition, funding efforts for the implementation of marine microalgal -omics resources and future perspectives are presented as well.

Caracterización <i>in silico</i> y análisis de la expresión de la subunidad alfa de la acetil-coenzima a carboxilasa heteromérica de dos microalgas

Las microalgas son microorganismos fotosintéticos con gran potencial para abastecer las demandas energéticas mundiales. Sin embargo, los limitados conocimientos que se tienen de estos organismos, en particular a nivel molecular de los procesos metabólicos, han limitado su uso con estos propósitos. En esta investigación se ha realizado el análisis in silico de la subunidad alfa de la acetil-Coenzima A carboxilasa heteromérica (αACCasa), una enzima clave en la biosíntesis de lípidos de las microalgas Chlorella sp. y Scenedesmus sp. Asimismo, se ha medido la expresión de este gen en ambas especies cultivadas en medios deficientes de nitrógeno. Los resultados indican que la αACCasa muestra conservación estructural y funcional en ambas especies de microalgas y su mayor similitud genética con otras especies de microalgas. Asimismo, se ha mostrado que el nivel de expresión del gen se incrementa significativamente cuando las microalgas son cultivadas en ausencia de nitrógeno, lo cual se relaciona a su vez con una mayor acumulación de lípidos microalgales. En conclusión, el análisis in silico de la αACCasa de Chlorella sp. y Scenedesmus sp. presentan características estructurales, funcionales y evolutivas muy similares con otras especies de microalgas y plantas. Asimismo, el estudio revela que en ambas especies el gen se sobreexpresa cuando las microalgas son sometidas a estrés por deficiencia de nitrógeno, el cual se relaciona significativamente con la acumulación de lípidos totales en estas células.

New molecular insights on the response of the green alga Tetraselmis suecica to nitrogen starvation

Microalgae are currently considered one of the most promising resources for biofuel production, aquaculture feedstock and new pharmaceuticals. Among them, green algae of the genus Tetraselmis are extensively studied for their lipid accumulation in nutrient-starvation conditions. In this paper, we present the full-transcriptome of Tetraselmis suecica and differential expression analysis between nitrogen-starved and -repleted conditions (at stationary phase) focusing not only on lipid metabolism but giving new insights on nutrient starvation responses. Transcripts involved in signal transduction pathways, stress and antioxidant responses and solute transport were strongly up-regulated when T. suecica was cultured under nitrogen starvation. On the contrary, transcripts involved in amino acid synthesis, degradation of sugars, secondary metabolite synthesis, as well as photosynthetic activity were down-regulated under the same conditions. Among differentially expressed transcripts, a polyketide synthase and three lipoxygenases (involved in the synthesis of secondary metabolites with antipredator, anticancer and anti-infective activities) were identified, suggesting the potential synthesis of bioactive compounds by this microalga. In addition, the transcript for a putative nitrilase, enzyme used in nitrile bioremediation, is here reported for the first time for T. suecica. These findings give new insights on T. suecica responses to nutrient starvation and on possible biotechnological applications for green algae.

Simultaneous nutrition removal and high-efficiency biomass and lipid accumulation by microalgae using anaerobic digested effluent from cattle manure combined with municipal wastewater

BACKGROUND

Microalgae as a viable biodiesel feedstock show great potential to approach the challenges of energy shortage and environment pollution, but their economic feasibility was seriously hampered by high production cost. Thus, it is in urgent need to reduce the cost of cultivation and improve the biomass and lipid production of microalgae. In this work, anaerobic digestion effluent from cattle manure combined with municipal wastewater was used as a cost-effective medium for cultivating microalgae and expected to obtain high biomass. The pretreatment of anaerobic digested effluent containing dilution rate, sterilization and nutrient optimization was investigated. Then, initial pH and light intensity for algal growth, lipid production and wastewater purification were optimized in this study.

RESULTS

Scenedesmus sp. could grow rapidly in 10% anaerobic digestion effluent from cattle manure combined with secondary sedimentation tank effluent without sterilization. Optimum nutrient additives for higher biomass were as follows: glucose 10 g/L, NaNO₃ 0.3 g/L, K₂HPO₄·3H₂O 0.01 g/L, MgSO₄·7H₂O 0.075 g/L and trace element A5 solution 1 mL/L. Biomass of 4.65 g/L and lipid productivity of 81.90 mg/L/day were achieved during 7-day cultivation accompanying over 90% of COD, NO₃ ^--N, NH₄ ⁺-N, and 79-88% of PO₄ ^3--P removal with optimized initial pH of 7.0 and light intensity of 5000 l×. The FAME profile in ADEC growth medium consisted in saturated (39.48%) and monounsaturated (60.52%) fatty acids with the 16- to 18-chain-length fatty acids constituting over 98% of total FAME.

CONCLUSIONS

This study proves the potential of anaerobic digested effluent combined with municipal wastewater for microalgae culture, and provides an effective avenue for simultaneous microalgal lipid production and treatment of two kinds of wastewater.

A differential k-mer analysis pipeline for comparing RNA-Seq transcriptome and meta-transcriptome datasets without a reference

Next-generation DNA sequencing technologies, such as RNA-Seq, currently dominate genome-wide gene expression studies. A standard approach to analyse this data requires mapping sequence reads to a reference and counting the number of reads which map to each gene. However, for many transcriptome studies, a suitable reference genome is unavailable, especially for meta-transcriptome studies which assay gene expression from mixed populations of organisms. Where a reference is unavailable, it is possible to generate a reference by the de novo assembly of the sequence reads. However, the high cost of generating high-coverage data for de novo assembly hinders this approach and more importantly the accurate assembly of such data is challenging, especially for meta-transcriptome data, and resulting assemblies frequently suffer from collapsed regions or chimeric sequences. As an alternative to the standard reference mapping approach, we have developed a k-mer-based analysis pipeline (DiffKAP) to identify differentially expressed reads between RNA-Seq datasets without the requirement for a reference. We compared the DiffKAP approach with the traditional Tophat/Cuffdiff method using RNA-Seq data from soybean, which has a suitable reference genome. We subsequently examined differential gene expression for a coral meta-transcriptome where no reference is available, and validated the results using qRT-PCR. We conclude that DiffKAP is an accurate method to study differential gene expression in complex meta-transcriptomes without the requirement of a reference genome.

Advances in metabolic modeling of oleaginous microalgae

Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.

Quorum sensing molecules in activated sludge could trigger microalgae lipid synthesis

Cultivating microalgae using wastewater is an economical strategy to produce biofuel; however, microbial contamination has to be controlled strictly. Microalgae lipid accumulation can be triggered by environmental pressures, and here, we studied whether microbial contamination is the pressure for microalgae. We hypothesized this pressure was forced via cell-to-cell communication with quorum sensing molecules (QSMs). In this work, we verified the impacts of QSMs produced by activated sludge (wastewater-born microbial consortiums) on both lipid content and biomass production of the microalgae Chlorophyta sp., since in combination, they determined lipid productivity. With QSMs stress, the lipid content of Chlorophyta sp. increased by ∼84%, while biomass production decreased only slightly. Consistently, enzymes on the fatty acid synthesis pathways were generally up-regulated, while they were slightly down-regulated for DNA replication. In summary, the total lipid production improved by 86%. These results revealed the positive effects of microbial contamination on microalgae biofuel production.

Leveraging algal omics to reveal potential targets for augmenting TAG accumulation

Ongoing global efforts to commercialize microalgal biofuels have expedited the use of multi-omics techniques to gain insights into lipid biosynthetic pathways. Functional genomics analyses have recently been employed to complement existing sequence-level omics studies, shedding light on the dynamics of lipid synthesis and its interplay with other cellular metabolic pathways, thus revealing possible targets for metabolic engineering. Here, we review the current status of algal omics studies to reveal potential targets to augment TAG accumulation in various microalgae. This review specifically aims to examine and catalog systems level data related to stress-induced TAG accumulation in oleaginous microalgae and inform future metabolic engineering strategies to develop strains with enhanced bioproductivity, which could pave a path for sustainable green energy.

Gene expression profiling of astaxanthin and fatty acid pathways in Haematococcus pluvialis in response to different LED lighting conditions

Haematococcus pluvialis is a green microalga of major interest to industry based on its ability to produce large amounts of astaxanthin. Biosynthesis of astaxanthin and its mono- and di-esters was significantly stimulated under 150 μmol m^-2 s^-1 of white LED (W-150) compared with lower light intensities, but the highest astaxanthin amounts were produced under 70 μmol m^-2 s^-1 of blue LED (B-70). Transcripts of astaxanthin biosynthesis genes psy, crtO, and bkt2 were upregulated under W-150, while psy, lcy, crtO, and crtR-B were upregulated by B-70. Total fatty acid content and biosynthesis genes fata and all dgat genes were induced under W-150, while C18:3n6 biosynthesis and dgat2a expression were specifically stimulated by B-70 which was correlated to astaxanthin ester biosynthesis. Nitrogen starvation, various LEDs and the identified upregulated genes may provide useful tools for future metabolic engineering to significantly increase free astaxanthin, its esters and fatty acid precursors in H. pluvialis.

Recent developments in synthetic biology and metabolic engineering in microalgae towards biofuel production

In the wake of the uprising global energy crisis, microalgae have emerged as an alternate feedstock for biofuel production. In addition, microalgae bear immense potential as bio-cell factories in terms of producing key chemicals, recombinant proteins, enzymes, lipid, hydrogen and alcohol. Abstraction of such high-value products (algal biorefinery approach) facilitates to make microalgae-based renewable energy an economically viable option. Synthetic biology is an emerging field that harmoniously blends science and engineering to help design and construct novel biological systems, with an aim to achieve rationally formulated objectives. However, resources and tools used for such nuclear manipulation, construction of synthetic gene network and genome-scale reconstruction of microalgae are limited. Herein, we present recent developments in the upcoming field of microalgae employed as a model system for synthetic biology applications and highlight the importance of genome-scale reconstruction models and kinetic models, to maximize the metabolic output by understanding the intricacies of algal growth. This review also examines the role played by microalgae as biorefineries, microalgal culture conditions and various operating parameters that need to be optimized to yield biofuel that can be economically competitive with fossil fuels.